Examining item usage is an important step in evaluating the performance of a computerized adaptive test (CAT). We study item usage for a newly developed multidimensional CAT which draws items from three PROMIS domains, as well as a disease-specific one.The multidimensional item bank used in the current study contained 194 items from four domains: the PROMIS domains fatigue, physical function, and ability to participate in social roles and activities, and a disease-specific domain (the COPD-SIB). The item bank was calibrated using the multidimensional graded response model and data of 795 patients with chronic obstructive pulmonary disease. To evaluate the item usage rates of all individual items in our item bank, CAT simulations were performed on responses generated based on a multivariate uniform distribution. The outcome variables included active bank size and item overuse (usage rate larger than the expected item usage rate).θ-values, the overall active bank size was 9–10%; this number quickly increased as θ-values became more extreme. For values of −2 and +2, the overall active bank size equaled 39–40%. There was 78% overlap between overused items and active bank size for average θ-values. For more extreme θ-values, the overused items made up a much smaller part of the active bank size: here the overlap was only 35%.For average Our results strengthen the claim that relatively short item banks may suffice when using polytomous items (and no content constraints/exposure control mechanisms), especially when using MCAT.The online version of this article (doi:10.1007/s11136-017-1624-3) contains supplementary material, which is available to authorized users. The underlying algorithm then selects the item that is most informative at that particular moment, given the current estimate of the latent trait value. It is clear why CATs appeal to healthcare professionals (HCPs): by selecting only those items that contribute most to the reliable measurement of a patient’s latent trait value, measurement efficiency is increased, which results in a substantial decrease in response burden )item usage.Since health-related quality of life (HRQL) has taken a central role in the evaluation of treatment interventions in patients with chronic obstructive pulmonary disease (COPD), we recently developed a multidimensional CAT (MCAT) to measure HRQL in patients with chronic obstructive pulmonary disease (COPD) . Followiθ), and items targeting average θ-values have a higher chance of being selected, all else being equal. If items are selected more frequently than could be expected based on chance or a predefined threshold, these items are typically referred to as being overexposed. Conversely, items selected less frequently than could be expected are referred to as underexposed. The terms item exposure and item usage seem to be used interchangeably in the literature. In the context of educational testing, item overexposure is seen as a threat to test security (examinees may be able to remember and share items with others) and receives a lot of attention in the literature e, e.g., . Howeverwithin-item and between-item multidimensional models. Within-item multidimensional models allow items to relate to more than one latent dimension. When between-item multidimensional models are used, the restriction is imposed that the items relate to one dimension only; multidimensionality is expressed through the correlations among the latent dimensions . In this study, we chose to use a between-item multidimensional model, since such models are useful when multiple distinct latent dimensions are measuredAdams et al.  divide malternate form equating or common-item equating). Each booklet contained items pertaining to at least two domains.Multidimensional calibrations are not currently available for the PROMIS general population sample, and therefore the PROMIS calibrations cannot be used in the current study. In order to facilitate multidimensional calibration, our test design needed to be constructed in a way that would allow for item parameter estimation as well as estimation of the covariance structure among the domains. We used a booklet design, whereby the total number of items was distributed among three booklets each containing around 100 items. The booklets were linked using ten anchor items per domain , and consisted of 52.7% men. More detailed patient characteristics are reported in Supplement 1.The following inclusion criteria were used: a medical diagnosis of COPD; sufficient oral and written mastery of the Dutch language; and being able to complete a questionnaire. HCPs  were recruited by JP, through his professional network. HCPs distributed the questionnaires accompanied by an information letter among COPD patients attending their clinics from October 2014 through December 2015. Of the 1500 printed booklets, 795 were returned by the end of December 2015. Our sample had a mean age of 67.2 years  for one or more of its categories. Following Paap et al. [All items in the item bank were scored on a 5-point Likert scale ranging from 0 to 4. In total, 10 different types of answer categories were used (depending on the domain and item formulation), for example, p et al. , for 55 The multidimensional graded response model was used to obtain item parameter estimates and estimates of the covariance structure.j in item i with m total response categories, x) is the logistic function,j < m.The probability of a response in category i: one discrimination parameter (denoted αi) and several βij parameters; the number of βij parameters equals the number of categories minus one. The βij parameter is related to the difficulty with which a respondent will reach the jth step of each item. Note that in unidimensional IRT, two types of parametrization can be used for x: αθ − β. In multidimensional IRT, α value for each dimension; here, only the αθ − β parametrization can be used. Some software packages, such as IRTPRO, calculate “easiness” rather than “difficulty” parameters. In IRTPRO, this parameter is denoted as c. The βij parameter described above equals the negative value of the c-parameter. The estimates of the item parameters and covariance structure were obtained using the software package IRTPRO [Up to five parameters were calculated for each item e IRTPRO .βij parameters showed a good spread (range: −7.57 to 7.67). Measurement precision for θ-estimates was excellent . The direction of bias was in line with the expected shrinkage (which is the result of the implementation of a Bayesian estimator): positive θ-values tended to be slightly underestimated and low negative θ-values tended to be overestimated. See Supplement 3 for RMSE and bias plots.A multivariate normal distribution was assumed for the four latent traits, with variances fixed to 1 and the covariances being estimated freely. The estimated correlation matrix among the four domains Φ equalled measures , and theθ-values—1000 for every increment of 0.2 on the multidimensional θ-scale between values −2 and 2. The Maximum A Posteriori (MAP) estimator was used in all simulations to estimate θ, at all stages of the CAT. The covariance matrix Φ estimated using the multidimensional GRM was used as a prior. Following Segall [Bayesian Volume Decrease, whereas Yao [Volume or Vm. One random item per domain was administered at the start in order to obtain initial θ-values to initialize the CAT. The CAT was terminated, when the termination rule (threshold standard error of measurement SE(θ) < 0.316)SE-threshold had been met for that dimension.CAT simulations were run with the package ShadowCAT  in R 3434. To evg Segall , item seg Segall  refer toreas Yao  simply aθ. Each of the outcome variables will be reported by domain as well as across domains . An item was considered overused when its usage rate was higher than the expected item usage rate,θ-value divided by the total bank size (194). Active domain/bank size was calculated as total domain or bank size minus items that were never used in the respective domain or overall bank.The outcome variables in this study were overuse and active domain/bank size, all conditional on θ-values. For average θ-values, the overall active bank size was 9–10%; this number quickly increased as θ-values became more extreme. For values of −2 and +2, the overall active bank size increased fourfold to 39–40%! Unsurprisingly, CATs for more extreme θ-values (−2 and +2) were generally longer than for less extreme values . However, the active bank size increased at a steeper rate than the test length, for increasing absolute θ-values. There was also considerable diversity in active bank size across domains. For average θ-values, the active domain size for fatigue and physical function was 5–6%, compared to 9–11% for ability to participate in social roles and activities, and 17% for the COPD-SIB. For extreme θ-values, almost all ability to participate in social roles and activities items were used; this finding can be directly linked to the item parameter distributions for this bank ; see Fig. The results of the CAT simulations are summarized in Tables θ-values—overused items dominated the active part of the multidimensional item bank; there was 78% overlap between overused items and active bank size. For more extreme θ-values, the overused items made up a much smaller part of the active bank size: here the overlap was only 35%.Comparing Table θ-values: FATIMP1 (“To what degree did you have to push yourself to get things done because of your fatigue?”), FAMTIMP9 (“How often did your fatigue make it difficult to plan activities ahead of time?”), FATIMP29 (“How often were you too tired to leave the house?”), PFB1 (“Are you able to climb up five steps?”), PFB44 , SRPPER20 , SRPPER23 ”), SGRQ12 , SGRQ13 , SGRQ26 (“I get afraid or panic when I cannot get my breath.”), SGRQ42R1a , and SGRQ42R1b .Figures 1–4 in Supplement 4 illustrate that there are 12 items that have relatively high item usage rates over a wide range of β parameter and thus cover a wider θ-range. A polytomous item can have more than one peak in its item information function, which would translate into more than one peak in the item usage plot. Longer CATs are needed to obtain reliable estimates of very low or high θ-values, which explains why as many as 38 items show relatively high item usage rates for low or high θ-values only.Some items, such as CSIB13 (“It frustrated me that I couldn’t do everything I wanted to do anymore”) and SGRQ31 (“Everything seems too much of an effort.”), show two peaks; something typical for polytomous data. Polytomous items have more than one θ-values.In Fig. In this study, we evaluated active bank size and item overuse/overexposure in a recently developed MCAT designed to measure HRQL in COPD patients using four correlated domains. Three generic PROMIS domains were used: the PROMIS domains fatigue, physical function, and ability to participate in social roles and activities , 26; as We used a multidimensional item bank consisting of 194 items (35–63 items per domain). Given that we developed a MCAT without content constraints and with no exposure control, our results indicate that the MCAT was working as intended: for average latent trait values, a small number of highly discriminating items was selected; for more extreme values, the item bank usage was more balanced. However, our results also showed that a relatively large part of the multidimensional item bank was never used (60%). The active part of the bank consisted of 77 items at most, across the four domains. This may indicate that—if these findings can be generalized—roughly 19 polytomous items per domain might suffice, when developing a multidimensional bank populated by items with high discrimination parameters that adequately cover the latent trait range of interest, and with high correlations among domains. Research focusing on unidimensional CATs has shown that CATs based on polytomous rather than dichotomous items can be performed with substantially smaller item banks; an item bank of 30 items may be sufficient for polytomously scored health outcomes , 39. OurItem usage has received little attention in the field of clinical  measurement so far. One exception concerns developing IRT/CAT-based short forms. Several authors have suggested that CAT simulations can be used to select the most appropriate items for inclusion in a short form –42. In tAnother topic which has received little attention in our field is the influence of capitalization on item calibration error. Since the item selection criterion most frequently used is a direct function of the discrimination parameter, item selection is sensitive to large standard errors of discrimination parameters , 45. TypWith this study, we extended the literature on item usage rates to multidimensional health measurement. We showed what happens when realistic CAT settings  are used: a relatively small number of highly discriminating items is selected. Currently, PROMIS item banks differ widely in length. Our results strengthen the claim that relatively short item banks may suffice when using polytomous items (and no content constraints/exposure control mechanisms), especially when using MCAT. This may be particularly relevant to item bank developers. However, if researchers or clinicians want to be able to influence the content , different item selection procedures are necessary; in such instances, a larger item bank will be needed.Supplementary material 1 (PDF 141 kb)Supplementary material 2 (PDF 371 kb)Supplementary material 3 (PDF 148 kb)Supplementary material 4 (PDF 638 kb)Below is the link to the electronic supplementary material.


The understanding of the correlation between structural and photoluminescence (PL) properties of self-assembled semiconductor quantum dots (QDs), particularly InGaAs QDs grown on (001) GaAs substrates, is crucial for both fundamental research and optoelectronic device applications. So far structural and PL properties have been probed from two different epitaxial layers, namely top-capped and buried layers respectively. Here, we report for the first time both structural and PL measurements from an uncapped layer of InGaAs QDs to correlate directly composition, strain and shape of QDs with the optical properties. Synchrotron X-ray scattering measurements show migration of In atom from the apex of QDs giving systematic reduction of height and enlargement of QDs base in the capping process. The optical transitions show systematic reduction in the energy of ground state and the first excited state transition lines with increase in capping but the energy of the second excited state line remain unchanged. We also found that the excitons are confined at the base region of these elliptically shaped QDs showing an interesting volume-dependent confinement energy scaling of 0.3 instead of 0.67 expected for spherical dots. The presented method will help us tuning the growth of QDs to achieve desired optical properties. In the last few years, significant attempts have been made to apply these QDs in realizing large-scale quantum processors2, large-area display3, solar cells beyond Shockley-Queisser limit4, and electronic-photonic devices6. Although QDs can be grown by various physical and chemical techniques ranging from Molecular Beam Epitaxy (MBE) to solution processing7, epitaxial QDs of semiconductors, grown in MBE on a single-crystal substrate having a specific crystallographic orientation, provide us with well-defined systems to correlate optical and structural properties. Indium-Gallium-Arsenide (InGaAs) QDs on Gallium-Arsenide (GaAs) (001) substrate, is the best candidate for mid and far infrared photodetectors and as the active material in photovoltaic fields and are the most studied system to understand structure-tunable optical emissions. A substantial amount of research work has been done to correlate emission-wavelength, line-shape and the effect of spin-orbit coupling in quantum yield of the QDs with the composition and strain profiles. The shapes of QDs, apart from size and structure tuning, have also been used as a controlling parameter to tune optical properties. The QDs of various shapes have been grown, like ellipsoidal8, lens10, pyramidal11, multi-faceted11 and quantum rings12. In all these studies17 optical signals were obtained from a buried layer, that reduces non-photonic transitions of exposed surface, and measurements of structural parameters namely composition, strain, size and shape were obtained from the capped top layer, with a key assumption that the buried and surface QD layers are identical in nature.Semiconductor quantum dots (QDs), where charge carriers are confined in all three directions on length scales of a few nanometers, resulting in discrete energy levels, are fascinating size-tunable photonic materials providing narrow line-width emissions18, segregation, faceting, intermixing, and strain-enhanced diffusion between layers of QDs near buffer and capped layers known to vary20 strongly affecting the confinement length of charge carriers within QDs that determine the characteristics of emitted photons17. Here we show, for the first time, that both structural and optical properties can be measured from same layer of QDs as a function of capping layer thickness. The atomic force microscopy (AFM) images obtained from uncapped QD sample enabled us to reconfirm the results obtained from synchrotron X-ray scattering measurements.However, it is becoming increasingly clear that this assumption is not in fact valid as In-Ga intermixing during growth of these two layers on GaAs (001) substrate, the buried-layer just above the buffer layer and the top-layer just below capping layer can be quite different. The process of strain release28 are ideal non-destructive techniques to extract the structural information of the nanometer-thin layer of QDs averaged over a large area depending on the footprint of the X-ray beam over a sample. GID studies reveal the average values of the structural parameters; composition, interfacial strain, lateral and vertical confinement lengths which are solely responsible for excitonic energy levels within QDs. The availability of intense synchrotron sources delivering nanometer-sized beams would enable us, in the future, to obtain information regarding composition and strain profiles averaged of a few tens of dots or perhaps an individual QD using the methods described in this paper. Here we present the results of uncapped and capped InGaAs QDs samples and the details of data analysis and measurements are given in the method section. It should be mentioned here that the volume of QDs on GaAs substrate is quite small, as a result only GID peaks like the (200), (220), (400) etc can be measured29 nondestructively. Measurement of other conventional diffraction peaks require much higher incidence angle and GaAs peaks overshadows the QD data as the X-ray beam penetrates deeper into the substrate. We optimized the sensitivity of QD signal by varying the incident angle and available energy of the X-ray beam for these measurements. The ratio of integrated intensity of the (200) and (400) profiles from GaAs to InAs in-plane reflection are measured here as a function of in-plane lattice parameters to extract indium profile within an average quantum dot.Grazing incidence diffraction (GID) X-ray measurementsθ’ with incident X-ray beam and 1D Mythen detector is kept at a detector angle (Φ) with respect to direct beam so that it is twice the incident angle of photons to crystal planes (Φ = 2θ) and the scattering geometry is shown in Fig. aII) defined in terms of the indices  of the nearest Bragg reflection of the substrate as θ’ values from the obtained scans have been stitched by Matlab programs to generate typical two-dimensional GID images around 400 and 200 Bragg peaks where vertical and horizontal axes denotes exit angle of Mythen detector (αf) and in-plane lattice parameter (aII) respectively. A representative 2D scattered intensity data around (400) Bragg peak of the uncapped InGaAs QDs is shown in Fig. aII values (0.565 nm for GaAs and 0.605 nm for InAs) exhibit intermixing and alloying of In and Ga within wetting layer (WL) and QDs. The results from AFM measurements presented here clearly show that the InGaAs QDs are ellipsoidal in shape with a preferred elongation in the direction perpendicular to the miscut stair-steps  are the lattice parameter of GaAs and of InGaAs obtained from Vegard’s law corresponding to Indium content x31. The calculated strain profiles shown in Fig. a’ for uncapped, 5 nm and 30 nm capped samples came out to be 24 nm, 29 nm and 32 nm respectively. The eccentricity values also increase with increasing capping thickness making buried QDs more elongated (refer Table The measurements of (400) and (200) in-plane crystal planes of the QDs samples around the GaAs bulk peaks were done by orienting the substrate at an angle ‘QDs Fig.  and cappQDs Fig.  and 30 nQDs Fig.  GaAs. ItaII close to GaAs and with increase in average QD height, aII approach the value of InAs lattice parameter. For uncapped QDs, refer representative data in Fig. aII values become 0.57 nm, 0.573 nm, 0.576 nm, 0.58 nm, 0.589 nm and 0.593 nm, respectively following equation  nm3 for x = 0.25. This reduces the thickness of the wetting layer of area 16667.7 nm2 allocated to each QD to about 1.6 nm - close to the observed difference of QD heights between X-ray and AFM measurements.The dimensions of the major and minor axes at the height of 1 nm in GID data comes out to be 48 nm and 26.7 nm giving eccentricity of 0.83 and only at the height of 1.9 nm we get the values of major and minor axes as 37 nm and 21.7 nm with eccentricity of 0.81, refer results of the uncapped sample shown in Fig. 33 to cross-check the dimensions of the QDs and the estimated thickness of the wetting layer. A representative image of an uncapped QD having height of about ~3.8 nm is shown in Fig. We have carried out systematic cross-sectional transmission electron microscopy (X-TEM) measurements35 earlier but direct correlations between PL energy and structural parameters were not investigated.With increasing height of QD, lateral dimensions reduce significantly and major and minor axes dimensions become 16 nm and 10.6 nm with eccentricity of 0.75 at the apex region of QD – this is also consistent with measured AFM value. The strain profile obtained from X-ray measurements has been indicated by the color-bar in the Fig. 36 involving ground state E1) and second excited state (E2) around 1297 meV, 1326 meV and 1356 meV respectively, as indicated by ‘A’, ‘B’ and ‘C’ in Fig. k = 0) degeneracy leading HH-band as effective valence band for optical transition. Therefore ‘A’, ‘B’ and ‘C’ has been correlated with transition lines between E1 and E2, here we observe stronger E1 and E2 lines for all the QD samples. The high incident excitation intensity used here to get micro-PL data may lead to such intensity reversal due to state filling effects37. As expected the PL emission from the uncapped QD sample was much weaker due to non-radiative emission process13 through surface states, compared to capped samples. We have used 10 points (red line) data smoothening for guide to eye and presented in Fig. 39 and similar emission from GaAs around 1490 meV for all the QDs samples were confirmed. The width38 of the emissions for all the samples were found to be around 20 meV  composition dependent bulk band gap energy, (ii) confinement size and shape dependent confinement energy and (iii) exciton binding energy. The lateral dimension of the QD elliptical lens becomes larger as the capping thickness increase. The excitonic confinement volume of the average QD elliptical lens can be written as, γ is 0.67 due to the fact that γ) reduce from 0.67 to 0.43 (for cuboid shape) and to 0.33 34. 40; we found γ to be 0.3 from the plot of the confinement energy variation with respect to confinement volume  can be used to calculate effective composition of V of QDs. For 30 nm capped QDs we get x = 0.26. Similarly for uncapped QDs, ground state PL energy of 1297 meV gives the value of Indium composition x = 0.22. It should be noted here that GID measurements also show larger Indium composition in uncapped QDs as compared to 30 nm capped QDs. The Indium composition obtained from PL measurement was found to be lower than the values obtained in GID measurements. This results indicate that excitons are near the base of the elliptical shaped QDs having lower Indium concentration; the confinement area of the excitons, as discussed below, also matched with the dimension of the base of QDs.The relationship between QDs structure and confined exciton energy levels are schematically shown in Fig. E2, E1 and EGS are found to be 32 meV and 29 meV. The energy spacing increases with capping thickness and become 36 meV and 33 meV for 30 nm capped QDs (refer Table E1 − EGS = 3π2ħ2/2 mL2) also reconfirmed the consistency of GID and PL measurements. For 33 meV separation observed in 30 nm capped QDs calculated value of L came out to be 60.3 nm - this is consistent with the obtained major axis of the elliptical base of QDs obtained in the GID measurements. The increase in capping thickness shift PL lines towards lower energy as compare to the uncapped sample; for example a shift of 7 meV and 3 meV for EGS and E1 was observed for 5 nm capping  nm over InAs QDs on GaAs (001) substrate. The samples were grown by Molecular Beam Epitaxy (MBE). After oxide desorption a 250 nm GaAs buffer layer was grown followed by 100 nm Si-doped GaAs layer to enhance the supply of more photo-excited carriers into the surface of QDs in order to obtain a stronger PL response. The substrate temperature was then lowered to 470 °C during eight minute growth interruption followed by an additional 10 nm of GaAs to separate the QDs from the doped GaAs layer. Then 1.8 monolayers (MLs) of InAs were deposited with a deposition rate of 0.027 µm/h at same temperature with constant Asnm. The average density of QDs in the X-ray beam foot-print was around 60 per μm2 as found by AFM measurements. The representative AFM image shown in Figure X-ray measurements were carried out with high beam energy (25 keV) to ensure sufficient X-ray penetration depth to probe buried QDs at Beamline P08 of Petra III, Synchrotron in DESY, Germany. A beam-defining slit of dimension As. The fractions x within QDs and WL as a function of measured aII values can be calculated by taking ratio of the integrated scattered intensity as,I400 and I200 have been measured by taking integrated scattered intensity over the detector exit angle αf.The atomic structure factors for 400 and 200 Bragg reflections for zinc blend crystal structure of θ, Φ) position around the radial intensity profile of (400) GID peak. At each position only incidence in-plane angle ‘θ’ was varied by keeping the detector angle fixed. During these scans radial momentum qr = (4π/λ) sin (Φ/2) remains constant but angular momentum [qa = (4π/λ) sin (θ − Φ/2)] changes depending on the variation of θ. The QDs are generally have been modeled as stacked of iso-strain circular discs3 but AFM measurement for the present samples clearly show elongated InGaAs QDs. Our analysis of the radial data presented here clearly shows that stack of iso-strain elliptical discs each having particular in-plane lattice parameters (aII) represent the data much better. The iso-strain length scale has been considered as, R(θ) = ab/(a − (a − b) cos (θ)), where ‘a’ and ‘b’ are the sets of major axes and minor axes respectively. The dimension of the set of  values were determined by fitting the measured angular scans data and it was noted that higher values of  are associated with base region of QDs and lower values of  are linked with apex of QDs. The scattering contribution from each such elliptical disc can be written as,r and only depend on Indium concentration value x. We have assumed14 for the fitting of each of aII radial data that two different discs contribute in the measured intensity profiles. This is known approach3 to take care of size distribution of the QDs and the fitted values of two major axes a of the fitted discs with relative contribution within bracket are shown in Table Lateral dimensions of QDs have been calculated by several angular scan measurements; each scan has a particular (mentclass2pt{minimmentclass2pt{minimaII can be calculated by analyzing Yoneda wing in the scattered intensity profile as a function of exit angle around 400 Bragg diffraction peak. The height ‘z’ above GaAs substrate for a fixed aII could be calculated from the position of first Yoneda maximum k denotes the wave number of the X-ray beam and αc is the critical angle for GaAs substrate. The calculated profiles of the four-process scattering31 and measured data for some representative aII for all three QDs samples have been shown in Fig. 42, to carry out these calculations.αm > 1and for αm > 1The height from the GaAs substrate of any elliptical discs with fixed In the above expression The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.


Biodiesel was produced from soybean oil using calcium oxide and cow bone as heterogeneous catalysts, through transesterification process. The soybean oil used was characterized using gas chromatography mass spectrometer (GCMS) and the cow bone catalyst produced was characterized X-ray fluorescence (XRF) spectrometer. The effects of the variation of methanol/oil mole ratio, catalyst concentration and reaction temperature on biodiesel yield during the transesterification of soybean oil were investigated. Reaction time of 3 h and stirring rate of 500 rpm were kept constant. Using Response Optimizer (Minitab 17), the optimum conditions for biodiesel production were established. It was observed that the calcination of cow bone catalyst enhanced its conversion to apatite-CaOH. Also, the results obtained showed that the performance trends of calcined cow bone catalyst and the conventional CaO catalyst were similar. Value of the data•The data on biodiesel production can be modelled to examine the relationship between the process variable  as it affects the yield of biodiesel.•The data could be used at investigating the relationship between the fatty acid profiles of soybean oil and the yield of biodiesel.•10P6O26H2) for biodiesel production.The given data will show authors in the field of material science and chemical engineering that the calcination of cow bone will enhance cow bone conversion to apatite-CaOH catalyst  was determined . Table 12Response surface experimental design  was employed to investigate the effects of variation of methanol-oil mole ratio, catalyst concentration and reaction temperature on biodiesel yield. Materials used include methanol , CaO , waste cow bones and soybean oil. Equipment used include gas chromatography mass spectrometer (Agilent Technologies 7890A GC System USA) for the determination of fatty acids profile of soybean oil, X-ray fluorescence (XRF) spectrometer for the identification and quantification of the elemental composition of CaO, uncalcined and calcined cow bones used.The waste cow bones were first washed in clean water to remove any dirt present. They were then crushed  and grinded into small particles which were then cooked for 4 h at 100 °C using a pressure pot containing water. The water used was replaced every 30 min to remove tissues, fat and any other impurity that might be present. The hot water was then completely removed and the bone chips were then dried in an oven at 105 °C for 1 h. The dry chips obtained were then further grinded into fine powder from using electric grinder to have a particle size of 100 µm. The fine powder obtained was calcined at temperature of 800 °C in an electric furnace for 4 h to ensure complete transformation of calcium compound into apatite 2 cooled Si(Li) detector with a resolution of 131 eV at, Mn Kα (5.9 keV) X-ray and a 6-sample turret  was used. XRF spectrometer operation was based on the emission of the excited elemental components of the given sample through the bombarding of the sample with high energy X-rays.Determination of the elemental composition of unclacined and calcined cow bone catalysts involved the use of XRF analysis. Phillips 1404 XRF Wavelength Disperse Spectrometer coupled with X-ray tube and a Rh anode (X-rays source) having HVPS 60 kV, 7.0 mA, a LNOil sample was introduced into GCMS at oven temperature of 60 °C using 99.99% Helium with column length of 30 m, column thickness of 0.25 µm and internal diameter of 0.25 mm. The column temperature was programmed to increase to 200 °C at the rate of 10 °C per minute. The flame ionization detector (FID) temperature was set at 220 °C. The fatty acid composition of the soybean oil used is shown in The chemical compositions of CaO, uncalcined cow bone catalyst and calcined cow bone catalyst are shown in


We find that the OPC films spontaneously form periodic microarrays that are distinguishable from general polycrystalline perovskite materials in terms of their crystal orientation, film morphology and electronic properties. X-ray diffraction patterns reveal that the film is strongly oriented in the (112) and (200) planes parallel to the substrate. This film is structurally confined by directional crystal growth, inducing intense anisotropy in charge transport. In addition, the low trap-state density (7.9 × 1013 cm−3) leads to strong amplified stimulated emission. This ability to control crystal orientation and morphology could be widely adopted in optoelectronic devices.Controlling crystal orientations and macroscopic morphology is vital to develop the electronic properties of hybrid perovskites. Here we show that a large-area, orientationally pure crystalline (OPC) methylammonium lead iodide (MAPbI Lead halide perovskites are developed for a number of optoelectronic applications. Here, Cho et al. use a thermal gradient to achieve directional crystallization of methyl ammonium lead iodide films. The periodic microarrays exhibit anisotropic charge transport properties. We used an ionic liquid2 are completely soluble and transform into perovskites with no intermediate structures2  as a solvent in which both methylammonium iodide (MAI) and PbIes2 ref. . Thus wees2 ref. , 25. We 2 (1:1 molar ratio) solution in MAFa (25 wt%) onto an indium tin oxide (ITO)-coated glass substrate. The liquid film was pulled at a constant velocity, V, through a thermal gradient, G, which was generated by local heating. The resultant structure has two distinct observable growth patterns: stripes (main backbones) that propagate and form along the thermal gradient, presumably due to Mullins–Sekerka instability2 , (002), (112) and (200) planes, respectively. 3 films, respectively; both show the tetragonal structure of the perovskites. We observed that the X-ray diffraction patterns of the aligned OPC perovskite films show strong peaks at 2θ=19.90° and 20.00° corresponding to (112) and (200) planes, respectively, and peaks at 2θ=40.42° and 40.64° corresponding to (224) and (400) planes, respectively. This indicates that MAPbI3 crystals in OPC films orient mainly along the (112) or (200) directions parallel to the substrate. Clearly, there is a preferential orientation of the crystals such that edges of the PbI6 octahedron are in contact with the substrate. From detailed X-ray diffraction analysis, we found peaks with nearly negligible intensities, with respect to the baseline signal, in the (110) and (002) planes, as well as other tiny peaks for different planes  of the crystallization process2 and the efficient intercalation of MAI molecules into the growing PbI2 framework. It is clear that the MAFa is a good solvent to dissolve PbI2 and more so for MAI− and Pb2+ and CH3NH3+ and I−, it dissolves PbI2 better than other common organic solvents such as DMF and DMSO. This might be partially responsible for the slow crystallization of lead halide during our directional crystallization process because of the low degree of supersaturated Pb2+ and X−. In addition, an excellent solubility of MAI in MAFa could be responsible for the efficient intercalation process of MA cations into the lead halide crystal frameworks, resulting in the formation of compact and homogeneous crystal nuclei. The initial PbI6 octahedral crystals could be rearranged in our ionic liquid systems by Ostwald ripeningWe demonstrate that thermal-gradient-assisted directional crystallization is a compelling strategy for confining crystal orientations. t planes . Interesding to 2 and  diffraction peak of PbI2, revealing the complete conversion of a perovskite film from precursors. In the case of aligned MAPbBr3 macro-wires, they exhibit typical X-ray diffraction patterns similar to those observed from polycrystalline films .In contrast to the OPC films, randomly oriented sperulitic films generally show X-ray diffraction patterns with a couple of major peaks corresponding to the (110), (002), (112) and (220) planes . Note thne films . The dif3 phase. This diffraction pattern corresponds to the entire area of the image as shown in 3. A small branch separated from the microarrays shows the same lattice spacing  is observed3435We investigated the steady-state optical properties of the aligned OPC films  in order−2  measurements were carried out on the OPC films after pumping with 35 fs laser pulses with tunable wavelengths in a cavity-free configuration. inset in , which c3 perovskite filmsNt=2ɛ0ɛrVTFL/qL2, where ɛ0 and ɛr are the absolute and relative dielectric constants, respectively, VTFL is the onset voltage of the trap-filled limit region, q is the elemental charge, and L is the thickness of the film. We measured ɛr of the OPC perovskite films by the capacitance-voltage measurement with an ITO/perovskite/Au structure. The dielectric constant, averaged in the frequency range from 100 kHz to 1 MHz, (plateau region) is 33.7±0.2  and two orders of magnitude lower than that observed for epitaxially grown perovskite films (∼1015 cm−3), but higher than that of single crystals (109 to 1010 cm−3)2 V−1 s−1 and a carrier density of ∼1.0 × 1012 cm−3  and normal to the backbones are shown in The electronic properties of perovskites strongly depend on the film morphology, crystallinity and crystal orientation. To investigate how the macroscopic alignment influences charge transport properties, we fabricated field-effect transistor (FET) devices with the aligned OPC films and characterized transport properties in different directions. Top-contact, bottom-gate phototransistor devices with p-SiIds−Vgs) of aligned OPC films measured along the direction of the main backbone as illustrated in IDS //) and along the direction normal to the backbone as depicted in IDS ⊥) under both white-light illumination (power density=0.5 mW cm−2) and dark conditions. Ids1/2 (p-channel) as a function of Vgs corresponding to Ids1/2 versus Vgs curve to extract the mobility (μ) and threshold voltage (Vth) with the standard equation of FET devices: Ids=(μWC0/2L) (Vgs−Vth)2, where W, C0 and L are the channel width, gate dielectric capacitance per unit area and channel length, respectively. The characteristics of FET devices using aligned films measured in the IDS // direction under illumination exhibit typical ambipolar behavior, with a hole mobility (μh) of 2.1±0.3 cm2 V−1 s−1 at 78 K  of those devices was ∼105. Note that the mobility we observed is an order of magnitude higher than that of previously reported polycrystalline perovskite films (μh=0.18±0.05 cm2 V−1 s−1 at 298 K) fabricated with the same device configurationIds on Vds at different Vgs, of the devices under illumination are shown in IDS⊥direction under illumination were markedly reduced to approximately 8.7 × 10−3 cm2 V−1 s−1 and 103, respectively  were observed at 298 K (IDS // direction showed lower mobilities (μh of ∼8 × 10−5 cm2 V−1 s−1) than those measured under illumination, but the Ion/off of ∼103 is still reasonable, whereas the devices measured with IDS⊥direction exhibited low device performances with negligible field effect and the Ion/off of ∼10 (IDS⊥direction (See IDS // under dark) worsen when measured at 298 K  than in case of IDS ⊥, but worse than in case of IDS //. Results from our measurement of the angle-dependent charge transport properties and the cross-sectional SEM analysis indicate that the anisotropic charge transport properties are dictated by the interconnection areas of the side branches  is an indicator of how efficiently an optoelectronic device responds to an optical signal, and is therefore an important figure of merit for evaluating the performance of phototransistors. It is given by R=(Ilight−Idark)/Elight, where Ilight and Idark are the channel currents under illumination and in dark, respectively, and Elight is the power of incident illumination. We measured photoresponsivity as a function of VGS in our phototransistors, finding a maximum R (at 78 K) along the direction of the backbone as 6.1 A W−1 (−1). This is consistent with the results of the transfer characteristics measured under dark and illumination conditions.Photoresponsivity  can be defined asTo explain the origin of the branched periodic micropatterns in OPC films, we present a simplified qualitative description of the formation process. We posit that the growth process is controlled by a temperature-dependent solvent evaporation rate, which produces supersaturation of the precursor molecules later consumed by their deposition onto crystal surfaces. The solid-liquid interface moves in the direction of temperature gradient (that is from higher to lower solvent evaporation rate). Consider a simple model of crystallization from a one-component molecular precursor solution. At higher evaporation rates, the concentration of the precursor at the solid–liquid interface, v is the volume of the precursor molecule in the crystal, K is the interface reaction rate (kinetic constant), and nGT is the Gibbs–Thomson concentration of the precursor molecules. If the pulling velocity on the film is greater than Vint, then more of the solution will be pulled into the higher temperature region with increased solvent evaporation rate. This will increase nint and subsequently increase the crystal growth rate. Consequently, the velocity of the interface increases until it enters an area where the concentration of the precursor at the interface decreases; thereafter, the velocity decreases. The process of Vint variation can be periodic due to the delay between the changes in nint and interface motion. We attribute the patterning of our crystalline film to this periodicity. In the presented description we do not consider crystal growth anisotropy, and the orientation of the growth front with respect to the direction of interface propagation. However, the outlined picture helps to understand the origin of the ripples on the crystal film surface as being due to a variation in the growth rate Vint. A more quantitative and detailed description taking into account the kinetic coefficient of anisotropy, the precursor diffusion in the solution and possible liquid dynamics is under investigation.where The recombination rates, carrier density and carrier mobility are inextricably linked together. Analysing different recombination mechanisms is crucial for designing specific strategies to alter each recombination rate by materials engineering. Identifying the dominant recombination process is also important for applications such as solar cells, light emitting diodes and lasers. The dynamics of different carrier recombination processes are described by the universal rate equation:34n is the carrier density, G is generation rate, and k1, k2, and k3 are monomolecular (due to excitonic or trap-assisted), bimolecular and Auger recombination rate constants, respectively. Regarding the carrier density dependent recombination rates, our results from the TA decay with varying pump fluence clearly revealed that the trap-state mediated monomolecular recombination is dominant at low pump fluences <6 μJ cm−2, and the higher order recombinations are dominant within the range of 9–80 μJ cm−2. In addition to the TA, a sharp transition from SE to ASE offers a framework for the dominant recombination pathways in the OPC films. Apparently, ASE is effective at a carrier density where k2 dominates over k1 and k3. The relationship between the bimolecular recombination and mobility is simply described by the traditional Langevin theory . The recombination rate of our OPC films derived from the Langevin theory is 1.2 × 10−6 cm3 s−1, which is several orders of higher than the reported values (10−10 to 10−11 cm3 s−1)43where μ) with scattering time (τs), where μ∝τs473 solids, acoustic phonon scattering has been considered as a main factor49T−3/2. This kind of acoustic phonon scattering is well established for non-polar semiconductors such as Si and Ge. However, care must be taken to generalize this to polar perovskites because other scattering sources may participate in the dissipation process. Recent reports revealed that polar longitudinal optical phonon modes could be a dominant source at high temperature in MAPbI3 filmsT+3/2. In other words, for most solution-processed materials, their mobility could have weaker temperature dependence than anticipated from pure phonon scattering models. Recently, charged point defects in MAPbI3 have been rigorously discussed3 films, which are attributed to the reduction in trap density. However, our relatively weak light illumination condition  is quite far from the situation of complete trap filling. We would expect the field effect mobility to be at least one order of magnitude higher if the traps were filled completely, which is quite unlikely for solution-processed materials because the grain boundaries and structural defects always exist regardless of illumination conditions. Therefore, even with perovskite systems of pure crystal orientation, the band-like conduction of charge carriers cannot be realized on the spatial scale of the actual FET devices by comparing the temperature dependence observed in the short-scale mobility of charge carriers.With low carrier densities, carrier scattering plays an important role in the charge transport. With the assumption of an ideal electron gas in the solid, the Drude model can describe the carrier mobility  and formic acid (98% assay) were purchased from Aldrich. Methylammonium iodide (MAI) was purchased from Dyesol. Lead iodide  was purchased from Alfa Aesa. All chemicals were used without further purification.++/SiO2 substrates . After blade coating at room temperature, the edge of the substrate (∼5 mm) was attached on top of the annealed metal bar by Kapton tape, as shown in The synthesis of MAFa has previously been described24I–V characteristics. TA decays were measured with a femto-nanosecond pump-probe setup. The detailed experimental setup has been described elsewhere54t) at higher excitation intensities, the data were fitted with a bi-exponential decay function (y=y0+A1ex−x0)/t1−(+A2ex−x0)/t2−, while at lower excitation intensities, the data were fitted with a single-exponential decay (y=y0+A1ex−x0)/t1−. The obtained time components are provided in The crystal structure of perovskite films was analysed using an X-ray diffractometer, Bruker AXS D8, with CuKα radiation. Absorption and photoluminescence were measured by a Varian Cary 5000 spectrometer and an Edinburgh FLS920, respectively. Keithley 2400 was used to perform −2) attached to the microscope of the probe station was applied as the light source. The dielectric constant measurement was carried out using a Keithley 4200 semiconductor parameter analyser at room temperature in dark condition. Direct current voltage was applied to the devices (ITO/Perovskite/Au) from −1 to +1 V in 0.02 steps. The applied frequency range was from 1 kHz to 1 MHz with 25 mV of alternating currentvoltage perturbation. All measurements were carried out under vacuum. Hall-effect measurements were performed using a Lakeshore model 665 system at room temperature on a 4-probe sample holder placed between the plates of an electromagnet. The samples were measured under a magnetic field varied in the 10–15 kG range.All ASE pumping experiments were conducted at room temperature. The one-photon pumping (650 nm) experiments were performed using a femtosecond laser system operated at a wavelength 800 nm with 35 fs pulses and a repetition rate of 1 kHz. A Quanta 200 FEG instrument was used to obtain SEM images. A TitanG2 80–300 instrument, FEI Co., Super Twin, x-FEG, operating at 300 kV was used for TEM analysis. The perovskite film dispersions in toluene were sonicated for five seconds, then deposited onto copper grids. Samples were dried in air for 1 h before measurements were taken. The phototransistor and photodetector were characterized using a Keithley 4200 semiconductor parametric analyser and a Signaton Micromanipulator S-1160 probe station. A white-light-emitting diode .Supplementary Figures 1-13, Supplementary Table 1 and Supplementary Notes 1 & 2.


Time-lapse in vivo microscopy studies of cellular morphology and physiology are crucial toward understanding brain function but have been infeasible in the fruit fly, a key model species. Here we use laser microsurgery to create a chronic fly preparation for repeated imaging of neural architecture and dynamics for up to 50 days. In fly mushroom body neurons, we track axonal boutons for 10 days and record odor-evoked calcium transients over 7 weeks. Further, by using voltage imaging to resolve individual action potentials, we monitor spiking plasticity in dopamine neurons of flies undergoing mechanical stress. After 24 h of stress, PPL1-α’3 but not PPL1-α’2α2 dopamine neurons have elevated spike rates. Overall, our chronic preparation is compatible with a broad range of optical techniques and enables longitudinal studies of many biological questions that could not be addressed before in live flies. Time-lapse imaging studies of more than a day in the fly brain have been infeasible until now. Here the authors present a laser microsurgery approach to create a permanent window in the fly cuticle to enable time-lapse imaging of neural architecture and dynamics for up to 10–50 days. Chronic preparations for long-term intravital microscopy exist for several animal model species that are either naturally translucent or allow installation of optical windows. Time-lapse studies using these preparations have revealed rich longitudinal dynamics for cellular morphology and function, under both natural and pathological conditions, that could not be captured by studying multiple distinct sets of animals at different time points4.Direct and repeated observations of cellular structure and physiology over extended periods in live animals are critical to dissecting the mechanisms of experience-dependent plasticity, neural development, degeneration, and aging6. Hence, many questions remain unanswered about how neural circuits develop, respond to experience or environmental influences, or degenerate due to injury or disease. To facilitate time-lapse studies of these issues, we developed a workflow for repeated, long-term in vivo imaging in the fly brain for up to 50 days  of the intact central nervous system has remained elusive due to the fly’s fragility and opaque exoskeletonays Fig. . As we i6. Using this microsurgery system, we opened an observation window in the cuticle of the fly’s head.First, we created a detachable mount that can hold an alert fly under a microscope objective lens by affixation of a silica fiber to the thorax Fig. . When he6, more than sufficient for creating the 150–250 μm diameter windows we made in the cuticle. However, when applied in isolation, laser microsurgery only allows in vivo brain imaging over 6–18 h time spans6. To enable long-term imaging studies, after creating the observation window we resealed the cuticle opening with transparent epoxy , and a few flies lived for up to 90 days  and the glue group (P = 0.06).To gauge the impact of surgery in more detail, we compared the lifespans of untreated control flies against those of flies that underwent either surgery and gluing of the cuticle (surgery group) or only gluing of the cuticle (glue group). Notably, female flies in the surgery and glue groups had a 100% survival rate at 10 days after surgery ; Fig. P = 0.06–0.8 for activity, P = 0.05–0.6 for speeds; Mann–Whitney U-tests with Holm–Bonferroni correction). These inconclusive findings, with contrary results from the ANOVA and post-hoc analyses, suggest there are mild short-term effects of the gluing procedure, detectable only at the limits of our study’s statistical power. Notably, the surgical procedures caused no additional detectable short-term harm beyond that of the gluing step.We first looked for potential short-term effects of surgery. Two days after surgery, the activity levels and walking speeds of flies in the two experimental groups and the control group were distinct . Later on, at Days 20 and 30 after surgery, flies in the three groups again had detectably different activity levels and mean walking speeds . However, as with the short-term effects of surgery, post-hoc analyses revealed that mean speeds and activity levels of the individual experimental groups were statistically indistinguishable from those of the control group . Of note, flies in both the surgery and glue groups had normal peak walking speeds and odor avoidance behavior for 30 days  in the MBON-α3 mushroom body output neuron, we repeatedly imaged the dendritic arbors of this neuron over periods of 8–10 days (2+ imaging experiments in flies that expressed the GCaMP6f Ca2+ indicator7 in mushroom body neurons (see Methods section). We measured odor-evoked Ca2+ responses in these neurons for up to 50 days over 18 imaging sessions. Throughout this period, cuticle windows stayed transparent and waveforms of the evoked Ca2+ transients remained consistent  of ~0.4/s. This estimated error rate is <7% of the mean rates of spontaneous spiking (~6–10/s) observed in PPL1-α’2α2 neurons.After expressing this indicator in the PPL1-α’2α2 dopaminergic neuron (see Methods section), we detected action potentials at single-spike resolution at the cell’s axonal region for up to 50 days  of the detected spikes in individual and groups of flies Fig. . These o11. These two types of dopamine neurons innervate different compartments of the mushroom body α/α’ lobes12 and have been implicated in the regulation of memory13, sleep14, and sensation15. Past studies have found that PPL1-α’2α2 but not PPL1-α’3 neurons contribute to the formation of both short- and long-term aversive memories13, whereas PPL1-α’3 but not PPL1-α’2α2 neurons have a wake-promoting function in sleep regulation14. However, it has remained unclear whether these two distinct types of PPL1 neurons have different long-term physiological responses to environmental influences.As a further demonstration of our ability to follow subtle physiological changes, we tracked the spiking properties of two types of PPL1 dopaminergic neurons (PPL1-α’3 and PPL1-α’2α2) in response to prolonged mechanical stress, which is commonly used in fly biology studies as a means of negative reinforcement or sleep deprivationUsing the Ace2N-2AA-mNeonGreen voltage indicator and our chronic preparation, we monitored the patterns of spontaneous spiking in the axonal regions of the two types of dopamine neurons in flies subject to a 4-day experimental protocol with daily imaging sessions Fig. . After lP = 4 × 10–4 and 0.01, respectively, n = 15 female flies; Friedman ANOVA), whereas these rates declined below baseline levels during the 2 recovery days   Fig. . ControlVA) Fig. . AnalyseVA) Fig. , indicat6.To enable longitudinal imaging studies of the adult fly brain, we created a chronic fly preparation that allows repeated intravital imaging of neural structure and dynamics across unprecedented intervals up to 50 days in duration. In female flies, our technique caused minimal-to-no detectable harm to the animal’s basic health and behavior. In male flies, our procedures led to a statistically significant decline in lifespan. Notwithstanding, our approach allows time-lapse studies in male flies over tens of days, a major improvement over past approaches that were limited to <24 h of imaging in adult fliesThe survival curve data indicate that the increased mortality of male flies is probably not a direct consequence of the laser treatment per se but more likely arises from the handling and related stressors that are part of the entire surgical and time-lapse protocol. Simply applying glue to the male fly led to a statistical decrease in lifespan that was indistinguishable from that of the entire surgical protocol Fig. . Althoug14, the increases we found in its spontaneous spiking and spike bursting activity after prolonged mechanical shaking might serve to induce a higher level of arousal in the face of a stressful environment. After the termination of mechanical shaking, activity rates in the PPL1-α’3 neuron gradually declined back to and then below baseline levels, which might reflect a rebound stage of sleep recovery. Although our observational data do not permit functional or causal interpretations, the data do show that the spontaneous dynamics of the PPL1-α’3 neuron reflect the fly’s history of stress over the past couple days, even after an environmental stressor has been removed.Our time-lapse voltage imaging studies in dopamine neurons revealed the differential responses of PPL1-α’3 and PPL1-α’2α2 neurons to prolonged mechanical stress. Given that the activity of the PPL1-α’3 neuron can promote wakefulness18. By combining our approach with recently developed robotic methods for automated fly handling19, it might be possible in the future to incorporate long-term intravital imaging into large-scale genetic screens based on assessments of fly neurophysiological or behavioral traits. Given the powerful genetic toolkits that already exist for use in fruit flies, our preparation for long-term imaging immediately opens new opportunities to investigate the molecular and cellular mechanisms of how individual neurons respond over time to environmental influences, change across the adult fly lifespan, or alter their properties due to brain disease.In addition to the optical techniques showcased here, our chronic fly preparation is compatible with a variety of recent optical imaging and optogenetic methods for use in head-fixed or freely moving fliesOK107-GAL4, R55D11-GAL4, 20×UAS-GCaMP6f, and 20×UAS-6×GFP flies from the Bloomington Stock Center. The FlyLight Project Team at Janelia Research Campus kindly provided MB304B-GAL4, MB093C-GAL4, and MB058B-GAL4 flies and the pJFRC7 vector plasmid. To create 20×UAS-Ace2N-2AA-mNeonGreen flies, we sub-cloned Ace2N-2AA-mNeon cDNA into the pJFRC7 vector using its XbaI and XhoI restriction sites20 and added a Drosophila Kozak sequence (CAAA) prior to the start codon of Ace2N-2AA-mNeon. A commercial transformation service (BestGene Inc.) inserted the pJFRC7-Ace2N-2AA-mNeon plasmid into the phiC31 docking site attP40, identified successful transformants, and provided us homozygous 20×UAS-Ace2N-2AA-mNeonGreen flies.We obtained 20×UAS-Ace2N-2AA-mNeonGreen flies, we dissolved all trans-retinal powder in 95% ethanol as the 20 mM stock and diluted it with fly food to 400 µM. We collected adult female flies (1–3 days old) after eclosion and transferred them to the 400 µM retinal food for 6–8 days before surgery.We performed all locomotion and imaging experiments using female flies (2–10-day old at the time of laser surgery). We raised flies on standard cornmeal agar media under a 12 h light/dark cycle at 25 °C and 50% relative humidity. To provide retinal to the To mount flies in preparation for either laser surgery and/or in vivo imaging, we anesthetized the flies by placing them on ice for 1 min and then transferred them to the cooled surface (∼4 °C) of an aluminum thermoelectric cooling block . Using a variety of pupil masks and 10-ns laser pulses, this system can cut holes in the fly cuticle with a range of diameters (~12–500 µm). After transferring a mounted fly to the surgery station, we created an optical window in the cuticle by laser drilling a 150-μm-diameter hole . This microsurgical procedure generally removed the cuticle, air sacs, and fat bodies and thereby exposed the underlying fluorescent cells  and cured it for 30 s to seal the cuticle opening. To maintain ~60% humidity surrounding the fly during the resealing process, we used a desktop ultrasonic humidifier  to puff humidified air directly onto the fly while it was under the dissection microscope. After sealing the opening, we released the mounted fly from the fiber as described above and returned the fly to a food vial for later usage.Overall, for each fly we required approximately ~3 min for mounting, ~1.5 min for laser surgery, and ~1.5 min for resealing of the cuticle. Some additional time was required for transferring flies, yielding an overall work speed of approximately eight flies per hour.To test the potential effects of laser microsurgery on fly viability, we measured the lifespans of three different groups of flies. The control group underwent no surgical treatments. The glue group received the UV glue atop the cuticle but no surgery. The surgery group underwent laser surgery and cuticle gluing. Each group comprised 25 male and 25 female flies. After the various treatments, we placed the individual flies into separate food vials. We recorded daily the number of living flies and transferred them to fresh food vials every 5 days. We kept the flies at 25 °C and 50% relative humidity, with a 12-h light/dark cycle.21. This assay was performed during the flies’ light cycle within a printed plastic chamber . The floor and ceiling of the chamber were each covered by a glass coverslip . An additional layer of Chromatography paper  was on the floor inside the chamber, allowing the flies to walk smoothly without slipping on the coverslip. Air or odor entered the chamber through two inlets (0.75 mm in width) at its left and right ends and exited through two outlets (0.75 mm in width) at its midpoint  and switched between clean air  and odor-containing air . After transferring a fly into the behavioral chamber, we first delivered air into both sides of the chamber for 1 min and then delivered 3% 4-methyl-cyclohexanol (MCH) into the left side for 1 min. Afterward, we delivered air again to both sides for 30 s and then 3% MCH into the right side for 1 min Fig. .To computationally track the movements of a fly in the behavioral videos, we performed an image analysis with the following four main steps Fig. . (1) We We classified the fly’s behavior into active states  and stationary states (<1 mm/s speed). We calculated the activity index as the fraction of the total session that the fly spent in an active state. For calculations of mean walking speed, we excluded from analysis all times when the fly was stationary. To calculate the odor avoidance index, we computed the ratio of the total time that the fly spent on the side of the chamber where the odor entered to that spent on the side with clean air Fig. .2, No. 0, Electron Microscope Sciences) above the fly’s head. On the top side of the coverslip, we glued a stainless steel washer (Belleville) to contain the water (~100 µL) used with a water-immersion objective lens . We used a 475/50 nm excitation filter (BrightLine), a 488 nm dichroic (Semrock), and a 534/30 nm emission filter (BrightLine). We illuminated the sample using the 480-nm wavelength module of a solid-state light source  with 5–10 mW of power at the specimen plane. We acquired images at 50 Hz, using a scientific-grade CMOS camera  to sample image regions of interest with 2 × 2 pixel binning.For imaging odor-evoked Ca2+ activity traces, we corrected the raw Ca2+ videos for any brain movement by using the Turboreg algorithm for image registration22 (http://bigwww.epfl.ch/thevenaz/turboreg/). We then selected pixels whose mean fluorescence intensity was in the top 10% of all pixels; we defined their union as the ROI over which we computed spatially averaged, time-dependent changes in relative fluorescence intensity, ΔF(t)/F0, where F0 was the mean fluorescence in the ROI averaged over the entire video. We corrected for photobleaching by fitting a double exponential function to the mean fluorescence trace, F0, and then normalizing F0 by the fitted double exponential trace.On each day, we presented five trials of 2% ethyl acetate to each fly through a glass capillary (0.35 mm inner diameter) ~1 mm in front of the fly’s antenna. Odor delivery lasted for 1 s and was followed by clean air for 19 s. To analyze the Ca2+ imaging. We used a 503/20 nm excitation filter (Chroma), a 518 nm dichroic (Chroma), and a 534/30 nm emission filter (BrightLine). We illuminated the sample using the 500-nm wavelength module of the solid-state light source  with 5–8 mW of optical power at the specimen plane. We acquired images at 1 kHz, using the scientific-grade camera and 2 × 2 pixel binning. For each fly, during each imaging session we sampled spontaneous neural activity during three separate recording trials, each 10 s in duration.To image voltage dynamics, we used a 1.0 NA, 20× water-immersion microscope objective lens  and the same custom epi-fluorescence microscope as for Ca2+ imaging to correct for brain motion, identify an ROI, extract a ΔF(t)/F0 trace, and correct for photobleaching. To identify individual action potentials, we high-pass filtered the ΔF(t)/F0 trace by subtracting a median-filtered (40-ms window) version of the trace and then identified as spikes the local peaks with amplitudes >3.5 s.d. of the mean baseline fluorescence8. We determined the SNR as the mean amplitude of the spikes divided by the mean value of the baseline fluctuations (1 s.d.) in fluorescence. We defined the burst ratio as the fraction of spikes with an interspike interval to the preceding spike of <20 ms. For each fly, we averaged each of these spiking activity metrics across the three 10-s recordings performed in each session; using the resulting mean values, we computed the box-and-whisker plots in Figs. To analyze the voltage traces, we used the same procedures described above for Ca9 to compute the spike detection fidelity, d′, in a way that takes into account both the duration and intensity of the fluorescence waveform in response to an action potential. We estimated the photon shot noise in the optical voltage signal as the standard deviation of the fluctuations in baseline fluorescence. We then computed d’ using the empirically determined, mean optical spike waveform (see equations S1–S4 of ref. 9).To analyze spike waveforms, we determined the mean waveform by averaging over all spikes within a trial. We then performed a spline interpolation  of the mean waveform and from the resultant determined the spike amplitude and full-width half-maximum value of the spike duration. We used a signal detection frameworkBefore experiments on mechanical stress, we separated the flies into individual food vials and allowed them to rest for 1 day. Then we put the vials on a compact digital mini-rotator (Thermo Scientific) with a rotating speed of 200 rpm for 1 day. Two more days of rest followed Fig. .U-test or Wilcoxon signed-rank test with a Holm–Bonferroni correction for multiple comparisons. In box-and-whisker plots, the boxes cover the middle two quartiles of each dataset, horizontal lines inside the boxes indicate median values, whiskers extend to 1.5 times the interquartile range, and individual points indicate outliers.We performed all statistical analyses using MATLAB (Mathworks) software. Sample sizes were chosen using our own and published empirical measurements to gauge effect magnitudes. We did not use a formal randomization procedure. However, at the start of each experiment we randomly selected flies in an informal manner from a larger group of flies that were raised together. We then performed surgery on the selected flies and used these same flies for all subsequent sessions within a given longitudinal experiment. Experimenters were not blind to each fly’s genotype. For statistical testing, we used the non-parametric Kruskal–Wallis ANOVA and Friedman ANOVA to avoid assumptions of normal distributions or equal variance across groups. For post-hoc pairwise comparisons, we used two-sided versions of Mann–Whitney Readers interested in either the experimental data or the software code used for analyses should please contact the corresponding authors.Supplementary InformationDescription of Additional Supplementary FilesSupplementary Movie 1


Because of this close link, gradual accumulation of Aβ into amyloid plaques has been reported in brain areas with intense neuronal activity, including cortical regions that display elevated activation at resting state. However, the link between Aβ and activity is not always linear and recent studies report exceptions to the view of “more activity, more plaques.” Here, we review the literature about the activity-dependent production of Aβ in both human cases and AD models and focus on the evidences that brain regions with elevated convergence of synaptic connections (herein referred to as brain nodes) are particularly vulnerable to Aβ accumulation. Next, we will examine data supporting the hypothesis that, since Aβ is released from synaptic terminals, β-amyloidosis can spread in AD brain by advancing through synaptically connected regions, which makes brain nodes vulnerable to Aβ accumulation. Finally, we consider possible mechanisms that account for β-amyloidosis progression through synaptically linked regions.Neuronal activity has a strong causal role in the production and release of the neurotoxic  Next, we will examine data in support to the idea that, since Aβ spreads through synaptically connected regions, the elevated concentration of synapses makes brain nodes vulnerable to Aβ accumulation. Lastly, we consider some possible mechanism to explain propagation and gradual accumulation of Aβ, which received little attention so far.First, we report studies that found Aβ accumulation. This hypothesis originates from evidences reporting that regions with elevated basal activity are more prone to accumulate Aβ aggregates [β generation and secretion [β species rises in the interstitial brain fluid (ISF) while awake or in conditions of active neurological status but decreases during sleep [β in vivo.One hypothesis that has emerged over the past decade suggests that intense neuronal activity makes brain regions more vulnerable to Agregates  and is secretion , 13. In ng sleep , 15, theThe idea of inactivity-vulnerability link received further support with studies that have modulated neuronal activity in specific brain regions of living AD mice.β levels in the barrel cortex, a neuronal circuit that receives physiological inputs from the vibrissae of mice [β in this region [β (and thereby amyloid plaques) in the same cortical region [β [A few studies investigated the effects of whisker manipulation on A of mice , 16, 17.s region . On the l region , 16, an β accumulation. ISF Aβ levels were increased more than 20% in the hippocampus after short pulses of PP light stimulation. Furthermore, postmortem immunohistochemistry revealed that repeated optogenetic stimulations over a 5-month period significantly increased the Aβ burden in the hippocampal DG.More recently, one study on A7 AD mice  used optβ species in activated and silenced regions, respectively.On the same experimental train of thought, another study  used a cβ levels has focused on the default mode network (DMN), a set of interconnected brain regions that are most active at resting state. Buckner and collaborators used functional magnetic resonance imaging (fMRI) to identify patterns of network activity and positron emission tomography (PET) with PIB compound to visualize amyloid deposits in elderly patients. Their studies reported spatial overlap between the topography of amyloid deposition and the regions of DMN  [β deposition. Also, Sperling et al. [β accumulation. We will come back to hyperactivity later in this paper.In humans, one important branch of studies on the impact of neuronal activity on Absystem) , 22. Usibsystem) , 24 foung et al. , 25 founε, an important risk factor for the development of late-onset AD [β and accelerates the processing of amyloid deposition [ε carriers depends on advanced amyloid deposition.However, hypoactivity has been also reported in some of DMN regions in healthy subjects carriers for APOEonset AD  . APOE iposition . As mentβ deposition, but the relationship between the two is not always linear. One longitudinal study [β deposits found that regions of high metabolic consumption in young adults overlap with regions of fibrils later in life, but this linear relation was not detectable in some of the brain regions that were included in the study. For instance, increased amyloid burden in the anterior cingulate cortex, medial frontal cortex, and lateral temporal cortex was not associated with a high metabolic rate during the lifespan. Conversely, visual cortex was spared by Aβ accumulation despite its high metabolic activity.Together, the above studies highlight strong correlations between neuronal activity of DMN and Aal study  that comβ deposition. Interestingly, the study also showed that primary sensory areas have relatively little connectivity, which could explain the reason for low Aβ depositions in the visual cortex despite intense activity in this region [One important clue to understanding this apparent paradox comes from studies on brain hubs, represented by nodes with an elevated number of connections, largely overlapping with heteromodal association cortices included in the DMN. Buckner and coworkers  run a cos region .β accumulation in active brain regions. In a study that directly explored this possibility through stepwise connectivity method in PIB-PET images, Sepulcre et al. [β accumulation. In particular, strong links were evident between the hippocampal region and orbitofrontal, lateral temporal, and posterior cingulate cortex.Hence, strong network connectivity rather than elevated baseline activation can be at the origin of vulnerability to Ae et al.  found coBero et al. replicated these results in an AD mouse model . By mappβ release [β accumulates in brain nodes is that Aβ peptides released from synaptic terminals gradually accumulate in the extracellular space of downstream regions.Since synapses are the principal sites of A release , 13, oneβ source on the hippocampus. In this study, APP Swedish/preselinin1 mice subjected to unilateral ablation of EC had 45% reduction in thioflavin-positive Aβ deposits in hippocampal DG of the lesioned hemisphere with respect to the control (nonlesioned) one. Since APP is axonally transported from EC neurons to nerve terminals in the DG through PP projections [β deposits in the DG. Using transgenic mice that overexpress FAD-linked mutant APP and PS1, the authors demonstrated that transection of PP is sufficient to decrease amyloid burden 2-3-fold in the hippocampus (and up to 5.5–10-fold in the DG) with respect to nonlesioned controls.This prediction has been confirmed at the synaptic circuits between EC and the DG. Sheng et al.  found thjections –36, Sisojections  asked ifβ domain restricted to the II and III layers of the EC. Aβ deposits, which were initially present only in the EC of these mice, became progressively evident in the DG, thereby leading the authors to argue that Aβ spread from the EC to the hippocampus. Even though the following paper discussed the validity of the APP-EC mouse model [β deposition was found to start from the subiculum and then spread in a time-dependent manner to synaptically connected brain regions , and this spreading pattern was abolished by ablation of the subiculum [A more direct evidence of spreading from EC to DG came from Mucke's group . These ase model , Harris'se model  was confse model , 41. In ubiculum .β is preferentially released at brain nodes and those connections between nodes represent preferential routes for the spreading of β-amyloidosis.Collectively, the above data indicate that Aα-synuclein in Parkinson and Tau in AD, see [β-amyloid protein. In this last section, we provide a short review of possible mechanisms involved in Aβ spread, which have been investigated over the last few years.The passage of disease-associated misfolded proteins from neuron to neuron is a key mechanism of progress in neurodegenerative diseases. Although the mechanisms of spreading have been clarified for some neurodegenerative diseases  of young and still plaque-free mice of the same transgenic strain [β deposition was found in proximity of some of the injected brain regions  and six months later Aβ deposits resembling amyloid plaques were also found in adjacent (and otherwise plaque-free) brain regions, indicating that Ab spreads from the injection site and gradually accumulates in other sites.In another study, Ac strain . Three mβ-amyloidosis. A set of experimental evidences excludes the possibility of an infectious process: (i) when other routes of Aβ extract administration are used  Aβ deposits are not evident in downstream regions [β depositions have not been found in mice expressing human APP wild-type, which is not prone to β-amyloidosis [β does not accumulate in brain regions that typically do not form plaques, for instance, cortical regions that receive projections from the striatum [This evidence raises the question of whether seeds trigger an infectious process that propagates within interconnected regions or rather if the seeds accelerate a process that would spontaneously occur in brain tissues that are prone to  regions  as wouldloidosis  . Similastriatum .β seeds can spread from one brain region to one other, likely passing through synaptic connections, this step is not sufficient to form deposits. Rather, Aβ only accumulates when seeds reach “receiving” regions that are prone to amyloidosis.Collectively, the above evidence indicates that although Aβ released into the extracellular space alters the physiological activity of downstream neurons. For instance, Aβ causes reduction of synaptic glutamate reuptake [β release from their dendrites [The above studies suggest that, even if the convergence of several synaptic inputs makes brain regions particularly vulnerable, factors associated with intrinsic properties of receiving regions are likely participating in the spreading of amyloidosis. No studies so far directly investigated this possibility, which is rather supported by indirect evidences showing that Areuptake  and/or ereuptake  that actendrites , 53.β release from downstream neurons.Hence, one possible scenario, which is worthy of future investigation, is that hyperactivity spreads from one brain region to synaptically connected one(s), thereby favouring activity-dependent Aβ accumulation. We suggest that most of the vulnerable regions in AD brain are nodes that receive high convergence of synaptic connections. One simple explanation for this vulnerability is that synaptic circuits are preferential routes for the release of Aβ, which then progressively accumulates at postsynaptic sites. But other factors intrinsic to neurons within the brain nodes can also contribute to β-amyloidogenesis through the spread of hyperactivity.We here provide one hypothetic model to explain the vulnerability of selected brain regions to AThis model raises questions which should be addressed in future studies. For instance, if the convergence of synaptic inputs makes brain nodes vulnerable, can we reduce the amount of synaptic inputs without interfering with general cognition? As a first step, this question could be addressed in AD mouse models using the abovementioned optogenetic strategies that allow to silence specific synaptic inputs in selected brain regions of behaving mice.Systemic administration of antiepileptic drugs can improve memory performance in patients at early AD stages , but wit


Let mentclass2pt{minimThe complete elliptic integrals function –10\docufunction –18. IndeRecently, the bounds for the complete elliptic integrals have attracted the attention of many researchers. In particular, many remarkable inequalities and properties for terature –52.p is a strictly monotonic function. It is well known that many important means are the special cases of the quasi-arithmetic mean. For example,In 1998, a class of quasi-arithmetic mean was introduced by Toader  which isof Gauss –60,\docder mean –70, and-Qi mean –74.Let pth power means of a and b, respectively. Then it is well known that the inequalityLet,1) From -1.3) we we1.3) wLet Motivated by inequalities  and the (see [Letbe continuous onand differentiable onandonIfis increasing (decreasing) onthen so are the functionsIfis strictly monotone, then the monotonicity in the conclusion is also strict.The inequalityholds for allLetTherefore, Lemma The following statements are true: The functionis strictly increasing fromontoThe functionis strictly increasing fromontoThe functionis strictly increasing fromontoThe functionis strictly decreasing fromontoThe functionis strictly decreasing fromontoParts (1) and (2) can be found in the literature [For part (3), let For part (4), let For part (5), let The functionis strictly decreasing fromontoLet From Lemma Therefore, Lemma LetandThen one hasfor allif and only iffor allif and only ifIt follows from  that2.1fined by  and LemmFrom Lemma Case 1ows from  and the Case 2ows from  and 2. Then  leads toLet LetThen the double inequalitieshold for allwithif and only ifandLet p). Then  and TheoThe double inequalityholds for allandIn this paper, we provide the sharp bounds for the special quasi-arithmetic mean In the article, we derive a new bivariate mean


Scientific Reports 10.1038/s41598-017-14330-y, published online 02 November 2017Correction to: This Article contains errors in the Results section under subheading ‘Biophysical characterization in HEK cells’.CrChR2 we speculated that a differently arranged inner gate could be responsible for the missing photocurrents. Therefore, we created the double mutant ChronosA80S E107R to reconstitute a serine residue at the putative inner gate while rendering the central gate anion conductive.”“Because Chronos exhibits no serine at the homologous position of S63, which is a main constituent of the inner gate in should read:CrChR2 we speculated that a differently arranged central gate could be responsible for the missing photocurrents. Therefore, we created the double mutant ChronosA80S E107R to reconstitute a serine residue at the putative central gate while rendering the central gate anion conductive.”“Because Chronos exhibits no serine at the homologous position of S63, which is a main constituent of the central gate in