Miracle-dz/UniFAR-FTUs huggingface dataset:
Indocyanine green fluorescence guided resection of parathyroid adenoma of the carotid sheath: a case report and review of the literature

Background Ectopic parathyroid tissue can pose difficulties in diagnosis, management, and resection of adenomas in patients with hyperparathyroidism. The use of multimodal pre-operative imaging is recommended due to the diverse anatomic presentation of parathyroid adenomas and the potential presence of multiple adenomas. Resection failure still can occur, however, indocyanine green (ICG) fluorescence imaging is an intraoperative tool that has potential to help address this challenge. In the case which follows we demonstrate the use of ICG fluorescence imaging to assist in successful resection of a parathyroid adenoma located within the carotid sheath. Case Description We present the case of a 75-year-old woman with primary hyperparathyroidism due to a parathyroid adenoma localized to the left carotid sheath, posterior to the carotid artery. Careful resection was aided by ICG fluorescence guidance allowing for complete resection and immediate postoperative restoration of normal parathyroid hormone and calcium levels. The patient had no peri-operative complications and had an unremarkable post-operative course. Conclusions The anatomical heterogeneity of parathyroid gland adenomas within and around the carotid sheath presents a unique diagnostic and surgical scenario; however, the use of intra-operative ICG, as presented in this case, has important implications for endocrine surgeons and surgical trainees alike. This tool provides improved intra-operative identification of the parathyroid tissue allowing for safe resection, especially in cases involving critical anatomical structures.
GJI Geomagnetism, rock magnetism and palaeomagnetism Inversion of time domain three-dimensional electromagnetic data

SUMMARY We present a general formulation for inverting time domain electromagnetic data to recover a 3-D distribution of electrical conductivity. The forward problem is solved using finite volume methods in the spatial domain and an implicit method (Backward Euler) in the time domain. A modified Gauss‐Newton strategy is employed to solve the inverse problem. The modifications include the use of a quasi-Newton method to generate a pre-conditioner for the perturbed system, and implementing an iterative Tikhonov approach in the solution to the inverse problem. In addition, we show how the size of the inverse problem can be reduced through a corrective source procedure. The same procedure can correct for discretization errors that inevidably arise. We also show how the inverse problem can be efficiently carried out even when the decay time for the conductor is significantly larger than the repetition time of the transmitter wave form. This requires a second processor to carry an additional forward modelling. Our inversion algorithm is general and is applicable for any electromagnetic field (E, H, d B/dt) measured in the air, on the ground, or in boreholes, and from an arbitrary grounded or ungrounded source. Three synthetic examples illustrate the basic functionality of the algorithm, and a result from a field example shows applicability in a larger-scale field example.
Least‐squares Estimation of an Unknown Number of Shifts in a Time Series

In this contribution, general results on the off‐line least‐squares estimate of changes in the mean of a random process are presented. First, a generalisation of the Hajek‐Renyi inequality, dealing with the fluctuations of the normalized partial sums, is given. This preliminary result is then used to derive the consistency and the rate of convergence of the change‐points estimate, in the situation where the number of changes is known. Strong consistency is obtained under some mixing conditions. The limiting distribution is also computed under an invariance principle. The case where the number of changes is unknown is then addressed. All these results apply to a large class of dependent processes, including strongly mixing and also long‐range dependent processes.
Prostate Cancer Metastasis to Stomach: A Case Report and Review of Literature

Metastatic prostate cancer is a common diagnosis with a protracted but terminal course. Gastrointestinal (GI) tract involvement is extremely rare, and reportedly portends a poor prognosis. It can present years after the initial prostate cancer diagnosis. Only fifteen cases of prostate cancer metastasis to the stomach have been reported in the literature. We report a case of a 72-year-old man with metastatic castration-resistant prostate cancer and extensive bony involvement. He presented a decade after the diagnosis of prostate cancer with signs of heartburn; a gastric biopsy was initially believed to represent primary gastric carcinoma, but subsequently a diagnosis of prostate cancer metastatic to the stomach was confirmed. This case highlights the importance of the provision of a pertinent clinical history and clinical differential diagnosis at the time of submission of surgical pathology specimens, as well as highlighting the need to have a low index of suspicion to pursue additional pathologic markers whenever a presumed second adenocarcinoma is noted in the context of a patient having a history of current or prior advanced-stage adenocarcinoma of another site. The correct diagnosis can shield the patient from the morbidity of inappropriate surgical or medical management.
Nonparametric density estimation : the L[1] view

Differentiation of Integrals Consistency Lower Bounds for Rates of Convergence Rates of Convergence in L1 The Automatic Kernel Estimate: L1 and Pointwise Convergence Estimates Related to the Kernel Estimate and the Histogram Estimate Simulation, Inequalities, and Random Variate Generation The Transformed Kernel Estimate Applications in Discrimination Operations on Density Estimates Estimators Based on Orthogonal Series Index.
Near-Ultraviolet InGaN/GaN Light-Emitting Diodes Grown on Patterned Sapphire Substrates

We describe the microstructure and optical properties of near-ultraviolet InGaN-GaN light-emitting diodes (LEDs) fabricated onto conventional and patterned sapphire substrates (PSSs) using metalorganic chemical vapor deposition. The PSS LED with an optimized hole depth (1.5 µm) shows an improvement of the room-temperature photoluminescence intensity by one order of magnitude compared with that of the conventional LED. As much as a 63% increased light emission intensity of the PSS LED was obtained at a forward current of 20 mA. For a typical lamp-form PSS LED (at 20 mA), the output power and external quantum efficiency were estimated to be 10.4 mW and 14.1%, respectively. The increase of the output power could be partly due to the improvement of the internal quantum efficiency upon decreasing the dislocation density, which was further confirmed by the transmission-electron-microscopy and etch-pit-density studies for the GaN-on-PSS samples. Moreover, the emitted light scattering at the GaN/PSS interface could also contribute to the enhancement of light extraction efficiency.
A latent‐factor self‐exciting point process for software failures

Software debugging is the process of detecting and removing bugs during software development. Although the intent of modifications to the software is to remove bugs, one cannot rule out the possibility of introducing new bugs as a result of these modifications. We consider a self‐exciting point process, which can incorporate the case of reliability deterioration due to the potential introduction of new bugs to the software during the development phase. In order to account for the unobservable process of introducing bugs, latent variables are incorporated into the self‐exciting point process models. The models are then applied to two data sets in software reliability and additional insights that can be obtained from these models are discussed. Our results suggest that the self‐exciting processes with latent factors perform better than the standard point process models in describing the behavior of software failures during the debugging process.
An Accurate Parameterization of the Infrared Radiative Properties of Cirrus Clouds for Climate Models

An accurate parameterization is presented for the infrared radiative properties of cirrus clouds. For the singlescattering calculations, a composite scheme is developed for randomly oriented hexagonal ice crystals by comparing results from Mie theory, anomalous diffraction theory (ADT), the geometric optics method (GOM), and the finite-difference time domain technique. This scheme employs a linear combination of single-scattering properties from the Mie theory, ADT, and GOM, which is accurate for a wide range of size parameters. Following the approach of Q. Fu, the extinction coefficient, absorption coefficient, and asymmetry factor are parameterized as functions of the cloud ice water content and generalized effective size ( Dge). The present parameterization of the single-scattering properties of cirrus clouds is validated by examining the bulk radiative properties for a wide range of atmospheric conditions. Compared with reference results, the typical relative error in emissivity due to the parameterization is ;2.2%. The accuracy of this parameterization guarantees its reliability in applications to climate models. The present parameterization complements the scheme for the solar radiative properties of cirrus clouds developed by Q. Fu for use in numerical models.
Scaling law for dynamical hysteresis of cavity solitons

By applying to a cavity soliton a control beam modulated in time, we study numerically the performance of the soliton as a flip–flop memory. The soliton is switched on and off periodically through a hysteresis cycle whose size increases dynamically with the modulation frequency. We show that the phenomenon is ruled by a scaling law with an exponent compatible with the theoretical value 2/3 predicted in much simpler systems in the low-frequency limit.
Multi-Objective Personalization of the Length and Skippability of Video Advertisements

In this paper, we study two features of digital video ads on content-streaming platforms: length and skippability. Working with vdo.ai , we conduct a field experiment and randomly assign users to the Skippable/Long and Non-Skippable/Short versions of the same ad. We find that compared to the Non-Skippable/Short ad, the Skippable/Long ad version in our study increases ad consumption but decreases video consumption. This substitution pattern between ad and video consumption leads to a challenge for platforms seeking to maximize both outcomes. To address this challenge, we develop algorithms for multi-objective personalization that use individual-level substitution patterns to optimize ad and video consumption. The results show that multi-objective personalized policies can significantly improve both ad and video consumption outcomes over single-objective policies. In particular, we show that compared to a single-objective policy optimized for video consumption, there exists a multi-objective policy on the Pareto frontier that increases ad consumption by 61% at the expense of only a 4% decrease in video consumption. Similarly, compared to the single-objective policy optimized for ad consumption, there is a multi-objective policy that increases video consumption by 47% while decreasing ad consumption by just 13%. We conclude by discussing the practical implications for platform decision-making in real time.
Closed-Form Asymptotics for Local Volatility Models

We obtain new closed-form pricing formulas for contingent claims when the asset follows a Dupire-type local volatility model. To obtain the formulas we use the Dyson-Taylor commutator method that we have recently developed in [5, 6, 8] for short-time asymptotic expansions of heat kernels, and obtain a family of general closed-form approximate solutions for both the pricing kernel and derivative price. A bootstrap scheme allows us to extend our method to large time. We also perform analytic as well as a numerical error analysis, and compare our results to other known methods.
On the Dynamic Stability of Cool Supergiant Atmospheres

We have developed a new formalism to compute the thermodynamic coefficient Γ1 in the theory of stellar and atmospheric stability. We generalize the classical derivation of the first adiabatic index, which is based on the assumption of thermal ionization and equilibrium between gas and radiation temperature, toward an expression that incorporates photoionization due to radiation with a temperature Trad different from the local kinetic gas temperature. Our formalism considers the important non-LTE conditions in the extended atmospheres of supergiant stars. An application to the Kurucz grid of cool supergiant atmospheres demonstrates that models with Trad ≃ Teff between 6500 and 7500 K become most unstable against dynamic perturbations, according to Ledoux' stability integral ⟨Γ1⟩. This results from Γ1 and ⟨Γ1⟩ acquiring very low values, below 4/3, throughout the entire stellar atmosphere, which causes very high gas compression ratios around these effective temperatures. Based on detailed non-LTE calculations, we discuss atmospheric instability of pulsating massive yellow supergiants, such as the hypergiant ρ Cas (Ia+), which exist in the extension of the Cepheid instability strip, near the Eddington luminosity limit.
A rigorous unidirectional method for designing finite aperture diffractive optical elements

We have developed a rigorous unidirectional method for designing finite-aperture diffractive optical elements (DOE’s) that employs a micro-genetic algorithm (µGA) for global optimization in conjunction with a 2-D Finite-Difference Time-Domain (FDTD) method for rigorous electromagnetic computation. The theory and implementation of this µGA-FDTD design method for normally incident TE illumination are briefly discussed. Design examples are presented, including a micro-lens, a 1-to-2 beam-fanner and a 1-to-3 beam-fanner.
Level-crossing statistics and production in low Reynolds number wall turbulence

Statistical properties at velocity level crossings are analysed in a low Reynolds number fully developed turbulent channel flow. Emphasis is placed on local production statistics conditioned by fixed amplitudes of the streamwise u and wall-normal v velocity components. Direct numerical simulations performed in large computational domains are used for this purpose. The Reynolds number based on the channel half width and the shear velocity varies from 180 to 1100. Particular attention is paid to correctly determine the conditional quantities at level crossings of u and v velocity fluctuations, to prevent biasing effects. Level crossings along the longitudinal x and spanwise z directions in homogeneous planes are introduced together with different characterisations, such as directional and contour crossings. The frequency of events detected at fixed thresholds follows a Gaussian model acceptably well. There is more level-crossing activity in the spanwise direction than in the streamwise. The mean conditional production distributions are dissymmetrical with respect to the level-crossing thresholds in the low buffer and viscous sublayers. These statistics differ significantly from a statistical model that assumes joint normality between u and v. There is a clear but relatively mild Reynolds number dependence of the conditional expected means of u and v that do not scale with inner, outer or mixed variables. The Reynolds number sensitivity of these statistics increases towards the edge of the wall layer.
Transient growth in strongly stratified shear layers

Abstract We investigate numerically transient linear growth of three-dimensional perturbations in a stratified shear layer to determine which perturbations optimize the growth of the total kinetic and potential energy over a range of finite target time intervals. The stratified shear layer has an initial parallel hyperbolic tangent velocity distribution with Reynolds number $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}\mathit{Re}=U_0 h/\nu =1000$ and Prandtl number $\nu /\kappa =1$ , where $\nu $ is the kinematic viscosity of the fluid and $\kappa $ is the diffusivity of the density. The initial stable buoyancy distribution has constant buoyancy frequency $N_0$ , and we consider a range of flows with different bulk Richardson number ${\mathit{Ri}}_b=N_0^2h^2/U_0^2$ , which also corresponds to the minimum gradient Richardson number ${\mathit{Ri}}_g(z)=N_0^2/(\mathrm{d}U/\mathrm{d} z)^2$ at the midpoint of the shear layer. For short target times, the optimal perturbations are inherently three-dimensional, while for sufficiently long target times and small ${\mathit{Ri}}_b$ the optimal perturbations are closely related to the normal-mode ‘Kelvin–Helmholtz’ (KH) instability, consistent with analogous calculations in an unstratified mixing layer recently reported by Arratia et al. (J. Fluid Mech., vol. 717, 2013, pp. 90–133). However, we demonstrate that non-trivial transient growth occurs even when the Richardson number is sufficiently high to stabilize all normal-mode instabilities, with the optimal perturbation exciting internal waves at some distance from the midpoint of the shear layer.
Monte Carlo Techniques for Stochastic Pert Network Analysis

AbstractThe choice of analytic, approximation, or Monte Carlo methods (and combinations thereof) as means of solving the stochastic PERT problem depends on the activity cumulative distribution functions, network configuration, computing resources available, and desired accuracy. When Monte Carlo methods are Indicated, there exist several techniques for improving accuracy and diminishing computational effort. In this paper the application of five such techniques is described: antithetic variates, stratified sampling, control variates,regression, and conditioned sampling. These techniques may be used separately or in combinations; their existence makes Monte Carlo methods much more attractive in the investigation of stochastic PERT networks.
ON SOME COMPLETE METRIC SPACES OF STRONGLY SUMMABLE SEQUENCES OF FUZZY NUMBERS

In this article we introduce and study the notions of Δ(r)-lacunary strongly sum- mable, Δ(r)-Cesaro strongly summable, Δ(r)-statistically convergent and Δ(r)-lacunary sta- tistically convergent sequences of fuzzy numbers. Consequently we construct the spaces of these four types of difference sequences and investigate the relationship among these spaces. Further we show that the spaces of Δ(r)-lacunary strongly summable and Δ(r)-Cesaro strongly summable sequences are complete metric spaces.
Observation of correlated atom-photon pairs on the single-particle level

Fakulta ¨tfur Physik, Universita¨t Konstanz, 78434 Konstanz, Germany~Received 10 June 1996; revised manuscript received 18 December 1996! We report on an experimental observation of correlated atom-photon pairs produced in an atom-opticalexperiment. The pairs are generated from an excited atom that spontaneously emit a single photon. Clearevidence for the pair identiﬁcation as well as correlation measurements in the atomic motion are reported. @S1050-2947~97! 50604-4#PACS number~s! : 42.50. Ct, 32.80. 2t, 03.65. Bz, 42.50. Vk
Development of the Perceived Adjustment Scale in Close Relationships (PASCR) in Turkish Individuals: Validity and Reliability Study

Abstract The aim of this study was to develop The Perceived Adjustment Scale in Close Relationships (PASCR) that measure the perceived dyadic couple adjustment in close relationships. For this purpose, a two-stage scale development process was followed. In the first stage, exploratory factor analysis and reliability analysis were carried out on 308 participants, while the confirmatory factor analysis and concurrent validity analysis were conducted on 392 participants in the second stage. As a result of the explanatory factor analysis, the scale was found to have a six-factor structure and these factors are called relationship satisfaction, sexual adjustment, cognitive adjustment, social adjustment, origin family relationships, and conflict-compromise adjustment. The confirmatory factor analysis determined that this structure adapts to an acceptable level. Concurrent validity analysis shown that PASCR had a good level in terms of variables aimed at measuring. The developed scale and sub -factors were discussed in line with the relevant literature and suggestions for use were presented.
Efficient special purpose linear programming for FIR filter design

A high efficiency special purpose linear programming algorithm for FIR filter design is introduced, This algorithm incorporates FFT and FIR zero-phase filters to assist in the computation. Compared to the general purpose linear programming, this special purpose linear programming produces large savings in the computing cost when used to design FIR filters. The savings increase with the length of the filter being designed.
Trends in order picking: a 2007–2022 review of the literature

ABSTRACT A literature review on the order picking process in warehouses is presented for delineating the trends in time of research topics in this field. A total of 269 journal papers published between 2007 and 2022 were retrieved from Scopus. After a methodological classification, descriptive analyses were performed on authors, journals, subject area and top publishing countries. Bibliometric tools were used to map the topics covered by the reviewed studies, categorise them and determine possible relationships. Papers’ contents were evaluated in terms of eight categories, including five typical issues of order picking systems, plus three aspects dealing with the characteristics of the application. Insights about the extent to which these aspects have been covered in the literature are derived; relationships between the various aspects of the picking process are also delineated. Suggestions for future research activities are finally deducted, offering researchers and practitioners strong bases for works on order picking systems.
DISPERSION-RELATION-PRESERVING FINITE DIFFERENT SCHEMES IN COMPUTATIONAL AEROACOUSTICS

Higher-order optimized upwind schemes based on the Dispersion-Relation-Preserving (DRP) method are developed and tested for the first-order linear wave equation. The numerical results show that the optimized upwind DRP scheme has less dissipation and/or dispersion errors than that of the standard sixth-order upwind scheme and the central DRP scheme. The advantage of the upwind DRP scheme becomes even greater for simulating short waves or waves with discontinuous initial waveform.