Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of Phrenic Nerve Block and Suprascapular Nerve Block in Amelioration of Ipsilateral Shoulder Pain after Thoracic Surgery: A Systematic Review and Network Meta-Analysis

Background and Objectives: Ipsilateral shoulder pain (ISP) is a common complication after thoracic surgery. Severe ISP can cause ineffective breathing and impair shoulder mobilization. Both phrenic nerve block (PNB) and suprascapular nerve block (SNB) are anesthetic interventions; however, it remains unclear which intervention is most effective. The purpose of this study was to compare the efficacy and safety of PNB and SNB for the prevention and reduction of the severity of ISP following thoracotomy or video-assisted thoracoscopic surgery. Materials and methods: Studies published in PubMed, Embase, Scopus, Web of Science, Ovid Medline, Google Scholar and the Cochrane Library without language restriction were reviewed from the publication’s inception through 30 September 2022. Randomized controlled trials evaluating the comparative efficacy of PNB and SNB on ISP management were selected. A network meta-analysis was applied to estimate pooled risk ratios (RRs) and weighted mean difference (WMD) with 95% confidence intervals (CIs). Results: Of 381 records screened, eight studies were eligible. PNB was shown to significantly lower the risk of ISP during the 24 h period after surgery compared to placebo (RR 0.44, 95% CI 0.34 to 0.58) and SNB (RR 0.43, 95% CI 0.29 to 0.64). PNB significantly reduced the severity of ISP during the 24 h period after thoracic surgery (WMD −1.75, 95% CI −3.47 to −0.04), but these effects of PNB were not statistically significantly different from SNB. When compared to placebo, SNB did not significantly reduce the incidence or severity of ISP during the 24 h period after surgery. Conclusion: This study suggests that PNB ranks first for prevention and reduction of ISP severity during the first 24 h after thoracic surgery. SNB was considered the worst intervention for ISP management. No evidence indicated that PNB was associated with a significant impairment of postoperative ventilatory status.
Tree-structured analysis of treatment effects with large observational data

Treatment effect in an observational study of relatively large scale can be described as a mixture of effects among subgroups. In particular, analysis for estimating the treatment effect at the level of an entire sample potentially involves not only differential effects across subgroups of the entire study cohort, but also differential propensities – probabilities of receiving treatment given study subjects’ pretreatment history. Such complex heterogeneity is of great research interest because the analysis of treatment effects can substantially depend on the hidden data structure for effect sizes and propensities. To uncover the unseen data structure, we propose a likelihood-based regression tree method which we call marginal tree (MT). The MT method is aimed at a simultaneous assessment of differential effects and propensity scores so that both become homogeneous within each terminal node of the resultant tree structure. We assess simulation performances of the MT method by comparing it with other existing tree methods and illustrate its use with a simulated data set, where the objective is to assess the effects of dieting behavior on its subsequent emotional distress among adolescent girls.
Effect of Circadian Rhythm Disturbance on the Human Musculoskeletal System and the Importance of Nutritional Strategies

The circadian system in the human body responds to daily environmental changes to optimise behaviour according to the biological clock and also influences various physiological processes. The suprachiasmatic nuclei are located in the anterior hypothalamus of the brain, and they synchronise to the 24 h light/dark cycle. Human physiological functions are highly dependent on the regulation of the internal circadian clock. Skeletal muscles comprise the largest collection of peripheral clocks in the human body. Both central and peripheral clocks regulate the interaction between the musculoskeletal system and energy metabolism. The skeletal muscle circadian clock plays a vital role in lipid and glucose metabolism. The pathogenesis of osteoporosis is related to an alteration in the circadian rhythm. In the present review, we discuss the disturbance of the circadian rhythm and its resultant effect on the musculoskeletal system. We also discuss the nutritional strategies that are potentially effective in maintaining the system’s homeostasis. Active collaborations between nutritionists and physiologists in the field of chronobiological and chrononutrition will further clarify these interactions. This review may be necessary for successful interventions in reducing morbidity and mortality resulting from musculoskeletal disturbances.
Estimating the Costs of Product Development Projects Based on External Data: The New Product Development Cost Benchmarking Method

Activities for the development of new products are essential for most companies, and the investments for such activities can be substantial. Estimating the costs for new product development (NPD) projects is a challenging process as uncertainty is usually high and comparable data is scarce. While manifold work is available about general cost estimation methods, the estimation of NPD is still underrepresented in the literature. Except the few existing approaches, mostly build exclusively on internal data from within the company. In this article, we contribute to this gap by introducing an NPD cost benchmarking method. This approach faces the data availability problem by incorporating publicly available data of competitors into a regression model to estimate the average NPD costs of particular products. It is shown how specific adjustments to the data used for the model are necessary. The adjustments of input data account for macroeconomic circumstances and intercompany differences in accounting standards and development processes. Other adjustments (through a parametric model that builds on the regression results) account for company- and product-specific cost requirements. Using the method, relevant NPD cost estimations can be made for early-phase product management. The main output of this article is the introduction of the NPD cost benchmarking method as a novel solution to the challenging process of NPD cost management.
Gain and differential gain of single layer InAs/GaAs quantum dot injection lasers

We present gain measurements and calculations for InAs/GaAs quantum dot injection lasers. Measurements of the modal gain and estimation of the confinement factor by transmission electron microscopy yield an exceptionally large material gain of 6.8(±1)×104 cm−1 at 80 A cm−2. Calculations including realistic quantum dot energy levels, dot size fluctuation, nonthermal coupling of carriers in different dots, and band filling effects corroborate this result. A large maximum differential gain of 2×10−12 cm2 at 20 A cm−2 is found. The width of the gain spectrum is determined by participation of excited quantum dot states. We record a low transparency current density of 20 A cm−2. All experiments are carried out at liquid nitrogen temperature.
Parametric excitation of slow magnetoacoustic waves in the solar corona due to photospheric periodic motions

We suggest that the periodic shaking of coronal magnetic field lines due to photospheric periodic motions may induce the parametric excitation of slow magnetoacoustic waves in short coronal magnetic structures (with length < 50−70 Mm). Considering the periodic shaking of field lines as an external transversal periodic action on the coronal plasma we show that the temporal behaviour of slow wave spatial Fourier harmonics in the low plasma β limit is governed by the Mathieu equation. Consequently, harmonics of slow magnetoacoustic waves with half the frequency of the photospheric driver have an exponential growth in time. The growth rate of slow waves is proportional to the amplitude of photospheric motions and to the value of the plasma β in the corona. The mechanism may explain the existence of slow magnetoacoustic waves at least in short coronal loop systems (Nightingale et al. 1999, Sol. Phys., 190, 249).
Late Triassic magmatic rocks in the southern East Kunlun Orogenic Belt, northern Tibetan Plateau: Petrogenesis and tectonic implications

ABSTRACT The East Kunlun Orogenic Belt (E-KOB) documents successive subduction and accretion processes of the Paleo-Tethyan Ocean. However, the tectonic regime of the E-KOB at the late orogenic stage remains ambiguous. This study presents new results of whole-rock geochemistry and zircon U-Pb-Hf isotopes of the Xidatan pluton in the southern E-KOB. Detailed investigation reveals that the pluton is composed of quartz monzodiorite, host monzogranite, and igneous microgranular enclaves (IMEs). Zircon U-Pb dating results suggest that they are coeval magmatic rocks emplaced at ca. 206–203 Ma. Geochemical studies reveal that the quartz monzodiorite and IMEs share a common magma source, evidenced by consistent compositions of major elements, congruently enriched LREEs and LILEs, and consistently moderately depleted HFSEs and HREEs. Enriched to slightly juvenile zircon Hf isotopes (εHf(t) = −4.24 to +0.49) indicate that the primitive magmas of the quartz monzodiorite and IMEs involve the addition of mantle-derived magmas. The quartz monzodiorite and IMEs have identical ages, and consistent isotope features with the host monzogranite, together with the observation of ingestion of xenocrysts from host felsic rocks into the IMEs indicating that they were produced through the mixing of the mantle-derived mafic magmas and host felsic magmas. In contrast, The host monzogranite has moderately high SiO2 and Na2O+K2O, but low Fe2O3 T and MgO contents. It shows crust-like trace element patterns such as strong enrichments in LREEs and LILEs, but remarkable depletions in HREEs. Along with enriched zircon Hf isotopes (εHf(t) = −3.51 to −0.25), the host monzogranite was most likely to have originated from partial melting of lower crustal mafic rocks induced by underplated mantle-derived magmas. Considering abundant Late Triassic igneous rocks across the E-KOB, these new data provide further evidence that the Late Triassic magmatism in the E-KOB may be related to the delamination of thickened orogenic root under an extensional setting.
InP HEMT and HBT applications beyond 200 GHz

InP HEMT and InP HBT offer significant performance advantages for applications that range from microwave and millimeter-wave to fast digital and optoelectronic circuits. The improved transport characteristics, high transconductance, and optical integration properties of these devices hold great benefit for wireless and fiber-optic communications, radar, passive imaging and radiometer systems. We present an overview of recent results for InP devices and integrated circuits, including the current status of TRW's InP HEMT and HBT device and MMIC performance. The migration to new materials and process technology will enable volume production capability for high-performance applications to 200 GHz and beyond.
On the Irrotational Flow Around a Horizontal Cylinder in Waves

Milne-Thomson's circle theorem is used to study the characteristics of the two-dimensional irrotational flow around a horizontal cylinder under long-crested waves. Even when the cylinder diameter is small compared with the wavelength, the circumferential velocity and pressure distributions are unsteady and differ markedly from those corresponding to uniform ambient flow with similar velocity and acceleration vectors.
A Model for Detecting Fungal Diseases in Cotton Cultivation using Segmentation and Machine Learning Approaches

— This research detailed a model for detecting fungal diseases via techniques for processing images of cotton leaves. The work allowed to develop a model based on the set of preprocessed data, to formulate the developed model, to simulate and evaluate the model. It is about detecting fungal diseases in cotton cultivation. The image data records were collected in an online data repository consisting of images of cotton leaves infected with fungal diseases and normal leaf images. In addition, other images of infected and uninfected cotton leaves were collected in cotton production fields in the Ségbana region in Benin Republic. The model was formulated based on watershed segmentation technique by applying Edge Detection algorithm and K-Means Clustering; and Support Vector Machine (SVM) for classification. The simulation was done using MATLAB with Image Processing Toolbox 9.4. The results gave an accuracy of 99.05%, specificity 90%, misclassification rate 0.95%, recall rate 99.5% and precision 99.5%. In addition, with less computational effort and in less than a minute, the best results were obtained, showing the efficiency of the image processing technique for the detection and classification of infected and uninfected leaves. It was concluded that this approach was applied to detect fungal diseases on cotton leaves to promote the production and harvest of good quality cotton and valuable cotton products.
Evaluation of Blood Biomarkers and Parameters for the Prediction of Stroke Survivors’ Functional Outcome upon Discharge Utilizing Explainable Machine Learning

Despite therapeutic advancements, stroke remains a leading cause of death and long-term disability. The quality of current stroke prognostic models varies considerably, whereas prediction models of post-stroke disability and mortality are restricted by the sample size, the range of clinical and risk factors and the clinical applicability in general. Accurate prognostication can ease post-stroke discharge planning and help healthcare practitioners individualize aggressive treatment or palliative care, based on projected life expectancy and clinical course. In this study, we aimed to develop an explainable machine learning methodology to predict functional outcomes of stroke patients at discharge, using the Modified Rankin Scale (mRS) as a binary classification problem. We identified 35 parameters from the admission, the first 72 h, as well as the medical history of stroke patients, and used them to train the model. We divided the patients into two classes in two approaches: “Independent” vs. “Non-Independent” and “Non-Disability” vs. “Disability”. Using various classifiers, we found that the best models in both approaches had an upward trend, with respect to the selected biomarkers, and achieved a maximum accuracy of 88.57% and 89.29%, respectively. The common features in both approaches included: age, hemispheric stroke localization, stroke localization based on blood supply, development of respiratory infection, National Institutes of Health Stroke Scale (NIHSS) upon admission and systolic blood pressure levels upon admission. Intubation and C-reactive protein (CRP) levels upon admission are additional features for the first approach and Erythrocyte Sedimentation Rate (ESR) levels upon admission for the second. Our results suggest that the said factors may be important predictors of functional outcomes in stroke patients.
Effective medium theory for elastic metamaterials in two dimensions

An effective medium theory is developed which goes beyond the quasistatic limit to accurately predict the unusual properties of certain elastic metamaterials in two dimensions. The theory's validity is numerically verified through band-structure calculations for three different elastic metamaterials. The theory shows that the effective bulk modulus ${\ensuremath{\kappa}}_{e}$, shear modulus ${\ensuremath{\mu}}_{e}$, and mass density ${\ensuremath{\rho}}_{e}$ can be made negative near resonances by choosing appropriate resonant scatterers, leading to eight possible types of wave propagation. The theory not only provides a convenient tool to search for new metamaterials with desired properties, it also gives a unified physical picture of these properties. Two examples are presented: one possesses large band gaps at low frequencies; the other exhibits two regions of negative refraction, i.e., one for both longitudinal and transverse waves and the other for longitudinal waves only.
Determination of cosmological parameters from cosmic shear data

We study how parameter error forecasts for tomographic cosmic shear observations are affected by sky coverage, density of source galaxies, inclusion of cosmic microwave background experiments, simultaneous fitting of nondark energy parameters, and the parametrization of the history of the dark energy equation-of-state parameter w(z). We find tomographic shear-shear power spectra on large angular scales (l 0.04. « less
Multiple periodicities in the solar magnetic field - Possible origin in a multiple-mode solar dynamo

The solar magnetic field is generated in an oscillatory mode with a 22 yr full period and gives rise to the 11 yr sunspot cycle. However, analyses of contemporary solar records, as well as other surrogate indicators of solar activity, suggest the presence also of longer term periodicities in the solar magnetic cycle. This paper suggests that the solar dynamo can operate in a multiply periodic state, with several periodicites being generated simultaneously at different depths in the convection zone. A simple two-layer model of the solar convection zone is used to illustrate the physical mechanism of spatially localized, multiple-periodicity-mode dynamo regeneration. The two layers are characterized by differences in their respective turbulent magnetic diffusivities. Although the magnetic modes interact with one another, each mode is produced large in one layer or the other, and has an oscillation period approximately equal to the time characteristic of magnetic diffusion across the layer. The observed complicated periodicity pattern in the solar magnetic field could be a combination of two (or more) dynamo modes generated in this manner. The calculations are carried out using a differential rotation model consistent with recent helioseismological measurements, illustrating the challenge to dynamo theory raised by those observational results.
Mixtures of Gamma Distributions With Applications

This article proposes a Bayesian density estimation method based upon mixtures of gamma distributions. It considers both the cases of known mixture size, using a Gibbs sampling scheme with a Metropolis step, and unknown mixture size, using a reversible jump technique that allows us to move from one mixture size to another. We illustrate our methods using a number of simulated datasets, generated from distributions covering a wide range of cases: single distributions, mixtures of distributions with equal means and different variances, mixtures of distributions with different means and small variances and, finally, a distribution contaminated by low-weighted distributions with different means and equal, small variances. An application to estimation of some quantities for a M/G/1 queue is given, using real E-mail data from CNR-IAMI.
Design and Analysis of Cross-Over Trials

Abstract This chapter provides an overview of recent developments in the design and analysis of cross-over trials. We first consider the analysis of the trial that compares two treatments, A and B, over two periods and where the subjects are randomized to the treatment sequences AB and BA. We make the distinction between fixed and random effects models and show how these models can easily be fitted using modern software. Issues with fitting and testing for a difference in carry-over effects are described and the use of baseline measurements is discussed. Simple methods for testing for a treatment difference when the data are binary are also described. Various designs with two or more treatments but with three or four periods are then described and compared. These include the balanced and partially balanced designs for three or more treatments and designs for factorial treatment combinations. Also described are nearly balanced and nearly strongly balanced designs. Random subject-effects models for the designs with two or more treatments are described and methods for analysing non-normal data are also given. The chapter concludes with a description of the use of cross-over designs in the testing of bioequivalence.
Vertical‐cavity surface‐emitting InGaAs/GaAs lasers with planar lateral definition

A planarity preserving method for the definition of vertical‐cavity surface‐emitting lasers (VC‐SEL) is described. A strained‐layer InGaAs quantum well VC‐SEL structure was grown and lasers were laterally defined using a tailored deep proton implantation process. In these lasers we obtained low threshold current densities of 1000 A/cm2 and efficient cw operation. This method facilitates large‐scale integration of VC‐SEL devices.
Charge‐carrier kinetics in semiconductors by microwave conductivity measurements

Theory and measurements of the conductivity and the (transient) photoconductivity in the microwave frequency range are presented. The theory is tested on noninvasive measurements of semiconductors with known properties, i.e., Si wafers, in a simple apparatus. Quantitative agreement between theory and experiment is found without the use of adjustable parameters. A contactless and accurate determination of the conductivity of Si wafers in a restricted conductivity range is proposed. The quantitative evaluation of photoconductivity measurements makes a detailed discussion of nonuniform photoconductivity possible. The requirements for reliable measurements of nonhomogeneous charge carrier kinetics are discussed.
Plant and Non-plant based Polymeric Coagulants for Wastewater Treatment: A Review

The major source of fresh water is rain, which ultimately streams down into oceans and rivers. This water is consumed by the human beings for various purposes. All the consuming channels of this water, such as domestic, industrial, agricultural etc. generate the wastewater. Furthermore, urbanization and population growth are also the prime contributors. The reason why this water is called wastewater is due to the presence of contaminants such as organic material, biological components and toxic compounds, hence they have adverse effect on human health. Conventionally, many of the inorganic materials have been used as coagulants to treat the wastewater as these compounds have the ability to alter the physico-chemical properties. The present paper reviews the polymeric coagulants used for wastewater treatment that are green, sustainable and efficient. Moreover, these natural polymeric coagulants are biodegradable, eco-friendly and without any adverse effects on human health.
Magnetosonic waves in the presence of a lower hybrid turbulence and plasma heating

A theoretical investigation has shown that energy could be fed into a microturbulence from an externally excited low frequency magneto‐acoustic source. A magnetosonic wave, normally undamped in a quiescent plasma, is shown to be damped in the presence of a lower hybrid microturbulence which in turn effectively heats the plasma ions. This process does not require any threshold amplitude of the external pump wave and therefore, very small amplitude waves can deposit their energy into the plasma unlike the usual parametric heating schemes which demand a minimum threshold amplitude.