Miracle-dz/UniFAR-FTUs huggingface dataset:
Metformin Does Not Improve the Reproductive or Metabolic Profile in Women With Polycystic Ovary Syndrome (PCOS)

To determine whether metformin, when given to women with polycystic ovary syndrome (PCOS), promotes folliculogenesis by prompting a drop in free sex steroids resulting in a compensatory follicle stimulating hormone (FSH) rise, we conducted a randomized, double-blind, placebo-controlled crossover clinical trial. Eight mid-reproductive age PCOS participants with mean obese body mass index (BMI) and normal glucose tolerance received 8 weeks of metformin, given in a step-up fashion to a maximum dose of 2000 mg daily or placebo with daily urine sampling, 4-6 weeks washout, and crossover to the remaining arm for 8 weeks. To confirm the effects of metformin on glucose and other metabolic markers, a hyperinsulinemic, euglycemic 3-dose clamp (physiologic: 30 mU/m2 per minute, high: 400 mU/m2 per minute) followed each treatment. Urinary FSH, luteinizing hormone (LH), or pregnanediol glucuronide (Pdg) did not differ by treatment. Glucose disposal, endogenous glucose production, BMI, ovulation rates, serum sex steroids, free fatty acids, and lipids did not significantly differ by treatment, despite good evidence for compliance with the protocol. During the clamp, high-dose insulin administration was associated with an acute drop in serum LH. We conclude that short-term, high-dose metformin exerts minimal effects on both metabolic markers and reproductive hormones in a small sample of overall morbidly obese women.
$g_{m}/I_{\rm d}$ Method for Threshold Voltage Extraction Applicable in Advanced MOSFETs With Nonlinear Behavior Above Threshold

A method is proposed for determining the threshold voltage in a MOSFET, based on the derivative of the gm/Id ratio with respect to the gate voltage, which theoretically originates from the unified charge-control model similar to the capacitance-derivative method. This yields threshold voltages significantly less affected by gate-voltage-dependent mobility and series resistance than linear-extrapolation techniques. Moreover, it is more physically adequate in the case of advanced MOSFETs with ultrathin dielectrics, thin SOI body, or double gate operation, featuring a gradual transition from the exponential to linear charge control. The robustness of the method is experimentally verified on FinFETs with different lengths.
Use of Inertial Sensors to Predict Pivot-Shift Grade and Diagnose an ACL Injury During Preoperative Testing

Background: The pivot-shift (PS) examination is used to demonstrate knee instability and detect anterior cruciate ligament (ACL) injury. Prior studies using inertial sensors identified the ACL-deficient knee with reasonable accuracy, but none addressed the more difficult problem of using these sensors to determine whether a subject has an ACL deficiency and to correctly assign a PS grade to a patient’s knee. Hypothesis: Inertial sensor data recorded during a PS examination can accurately predict ACL deficiency and the PS score assigned by the examining physician. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: A total of 32 patients with unilateral ACL deficiency and 29 with intact ACLs in both knees had inertial sensor modules strapped to the tibia and femur of each limb for preoperative PS testing under anesthesia. Support vector machine (SVM) methods assessed PS grades on the basis of these data, with the examiner’s clinical grading shift used as ground truth. A fusion of regression and SVM classification techniques diagnosed ACL deficiency. Results: The clinically determined PS grades of all 122 knees were as follows: 0 (n = 69), +1 (n = 23), +2 (n = 27), and +3 (n = 3). The SVM classification analysis was 77% accurate in correctly classifying these grades, with 98% of computed PS grades falling within ±1 grade of the clinically determined value. The system fusion algorithm diagnosed ACL deficiency in an individual with an overall accuracy of 97%. This method yielded 6% false negatives and 0% false positives. Conclusion: This study used inertial sensor technology with SVM algorithms to accurately determine clinically assigned PS grades in ACL-intact and ACL-deficient knees. By extending the assessment to a separate group of patients without ACL injury, the inertial sensor data demonstrated highly accurate diagnosis of ACL deficiency.
Robust Energy Detection Based on Bayesian Estimation for Cognitive Radio

The energy detection is recently studied extensively as a promising candidate for primary signals detection in cognitive radio. However, one fundamental disadvantage of energy detection is that its performance degrades in the presence of inaccurate knowledge of noise power (noise uncertainty) which inevitably occurs in practical implementations. In this paper, we introduce a novel Bayesian estimation based energy detection (BEED) which, confirmed by simulations, can almost completely eliminate detrimental effects of noise uncertainty. In addition, the consistency of BEED is proved which means that it will correctly detect primary users with probability one when the sampling number increases to infinity.
Effectiveness of differential evolution in training radial basis function networks for classification

Building classification models often presents a significant problem that requires the selection of a classifier and a corresponding training approach. Radial basis function networks are a frequent choice among the classifiers for which a large spectre of training approaches exist. In that regard, an important role is played by bio-inspired methods, and differential evolution, as an representative example, has been applied for training such networks. This paper investigates the behaviour of differential evolution in training radial basis function networks primarily from the perspective of fitting the model to available (training) data rather than its performance on unknown (testing) data. This is believed to provide a clearer insight into optimiser efficiency. Another important issue considered is a steady emergence of new bio-inspired methods claiming superior performance that can be witnessed in the literature. It may raise the question whether differential evolution is still competitive to those approaches. In light of this, the canonical differential evolution algorithm has been compared to a couple of recently proposed and a well established swarm intelligence algorithm.
Serum FGF-21 Levels in Type 2 Diabetic Patients

Background. Fibroblast growth factor (FGF)-21 has been recently characterized as a potent metabolic regulator, but the physiological role of FGF-21 remains poorly understood. This study was designed to investigate serum FGF-21 levels in type 2 diabetes mellitus (T2DM) patients and explore the correlations between its serum levels and various cardiometabolic parameters in humans. Methods. Fifty-four newly diagnosed patients with T2DM (NDDM), 54 subjects with long duration of T2DM (LDDM), that is, more than 5 years, and 35 normal controls participated in this study. Fasting serum FGF-21 levels were measured using ELISA kits. The anthropometric parameters, glucose, glycosylated hemoglobin A1c, lipids, insulin, and high-sensitive C-reactive protein (hsCRP) levels were also measured in fasting status. Results. Serum FGF-21 levels were significantly higher in patients with NDDM and LDDM than in controls (361.80 ± 140.28 pg/mL and 351.17 ± 133.44 pg/mL vs. 185.89 ± 59.29 pg/mL, both p < 0.01), but there was no difference in serum FGF-21 levels between NDDM and LDDM. Fasting serum FGF-21 was found to correlate positively and significantly with age, waist-to-hip ratio, systolic blood pressure, fasting plasma glucose, glycosylated hemoglobin A1c, homeostasis model assessment (HOMA) of insulin resistance, and hsCRP, but negatively with HOMA of β-cell insulin secretion. Furthermore, multiple regression analyses showed that fasting insulin, HOMA of insulin resistance, low-density lipoprotein cholesterol, and hsCRP were independent factors influencing serum FGF-21 levels. Logistic regression analyses demonstrated that serum FGF-21 was significantly associated with T2DM. Conclusions. Serum FGF-21 levels were significantly increased in patients with T2DM. They may play a role in the pathogenesis of T2DM.
Model of Incoming Waves at Base Station to Evaluate the Performance of Intersector Soft Handover

A propagation model is needed to evaluate the performance of handover in mobile-communication systems. Generally, the received signal level from base stations (BSs) is calculated assuming path loss, and a lognormal (shadow)-fading model is used for evaluating intercell handover. The lognormal fading was assumed to be uncorrelated between cells. However, since the correlation between sectors is not clarified, an appropriate shadow-fading model to evaluate intersector handover has not yet been proposed. To obtain shadow-fading characteristics between neighboring sectors, the change in signal level and the direction of arrival of incoming waves at a BS must be clarified. This paper proposes a simple model of incoming waves to evaluate the performance of intersector handover. The validity of the proposed model is confirmed by comparing the difference between signal levels in BS sectors that are calculated using the proposed model and the measured power azimuth spectrum.
A dynamic target volatility strategy for asset allocation using artificial neural networks

ABSTRACT A challenge to developing data-driven approaches in finance and trading is the limited availability of data because periods of instability, such as during financial market crises, are relatively rare. This study applies a stability-oriented approach (SOA) based on statistical tests to compare data for the current period to a past set of data for a stable period, providing higher reliability due to a more abundant source of data. Based on an SOA, this study uses an artificial neural network (ANN), which is one of the commonly applied machine learning algorithms, for simultaneously forecasting the volatility and classifying the level of market stability. In addition, this study develops a dynamic target volatility strategy for asset allocation using an ANN to enhance the ability of a target volatility strategy that is established for automatically allocating capital between a risky asset and a risk-free cash position. In order to examine the impact of the proposed strategy, the results are compared to the buy-and-hold strategy, the static asset allocation strategy, and the conventional target volatility strategy using different volatility forecasting methodologies. An empirical case study of the proposed strategy is simulated in both the Korean and U.S. stock markets.
Influence of aged conductor surface conditions on AC corona discharge with a corona cage

Relatively little investigation has previously been done on the effects of aging on conductor surface conditions, or on the ac corona discharges from these conductors. In the present work these were investigated by means of comparing corona on typical aged conductors with that on new ones. The aged conductors from the ac power transmission lines had been in service for 12, 15 and 20 years. Scanning electron microscopy (SEM) and energy-dispersive X-ray (EDX) analysis were employed to characterize the surface morphology and composition of the conductors; and a non-contact surface profiler was used to measure the surface roughness of the six samples. As a result of corrosion and the adherence of various substances to the conductors, their surfaces were far rougher than the new ones. The ac corona discharge characteristics of these conductors were studied in a small corona cage using an ultraviolet imaging detector. As a result of the rough surfaces, the corona discharge intensity for the aged conductors was found to be much stronger than that for the new ones; and the corona inception voltages for the aged conductors were 10 to 25% lower than the new ones.
Forests synchronize their growth in contrasting Eurasian regions in response to climate warming

Significance Forests dominate carbon fluxes in terrestrial ecosystems. We demonstrate how an intensified climatic influence on tree growth during the last 120 y has increased spatial synchrony in annual ring-width patterns within contrasting (boreal and Mediterranean) Eurasian biomes and on broad spatial scales. Current trends in tree growth synchrony are related to regional changes in climate factors controlling productivity, overriding local and taxonomic imprints on forest carbon dynamics. Enhanced synchrony is becoming a widespread, although regionally dependent, phenomenon related to warmer springs and increased temperature variability in high latitudes and to warmer winters and drier growing seasons in mid-latitudes. Forests play a key role in the carbon balance of terrestrial ecosystems. One of the main uncertainties in global change predictions lies in how the spatiotemporal dynamics of forest productivity will be affected by climate warming. Here we show an increasing influence of climate on the spatial variability of tree growth during the last 120 y, ultimately leading to unprecedented temporal coherence in ring-width records over wide geographical scales (spatial synchrony). Synchrony in growth patterns across cold-constrained (central Siberia) and drought-constrained (Spain) Eurasian conifer forests have peaked in the early 21st century at subcontinental scales (∼1,000 km). Such enhanced synchrony is similar to that observed in trees co-occurring within a stand. In boreal forests, the combined effects of recent warming and increasing intensity of climate extremes are enhancing synchrony through an earlier start of wood formation and a stronger impact of year-to-year fluctuations of growing-season temperatures on growth. In Mediterranean forests, the impact of warming on synchrony is related mainly to an advanced onset of growth and the strengthening of drought-induced growth limitations. Spatial patterns of enhanced synchrony represent early warning signals of climate change impacts on forest ecosystems at subcontinental scales.
Functional MRI localisation of central nervous system regions associated with volitional inspiration in humans

1 Functional magnetic resonance imaging (fMRI) provides a means of studying neuronal circuits that control respiratory muscles in humans with better spatial and temporal resolution than in previous positron emission tomography (PET) studies. 2 Whole brain blood oxygenation level‐dependent (BOLD) changes determined by fMRI were used to identify areas of neuronal activation associated with volitional inspiration in five healthy men. Four series of scans of each subject were acquired during voluntary breathing (active task) and mechanical ventilation (passive task). Ventilation and end‐tidal PCO2 were similar between tasks. Scan data were re‐aligned to correct for movement artefacts and cross‐referenced breath by breath to respiratory data for selective averaging of inspiratory and expiratory images. 3 Group analysis identified significant increases in the fMRI signal with volitional inspiration in the superior motor cortex, premotor cortex and supplementary motor area at loci similar to those detected in earlier studies that used PET. Additional regions activated by volitional inspiration included inferolateral sensorimotor cortex, prefrontal cortex and striatum (these foci were only revealed by PET under significant inspiratory load). 4 This study represents the first synchronised breath‐by‐breath analysis of respiratory‐related neuronal activity with whole brain imaging in humans. Temporal resolution is sufficient to distinguish individual breaths at a normal breathing frequency.
Age‐specific patterns of unsatisfactory results for conventional Pap smears and liquid‐based cytology: data from two randomised clinical trials

Please cite this paper as: Castle P, Bulten J, Confortini M, Klinkhamer P, Pellegrini A, Siebers A, Ronco G, Arbyn M. Age‐specific patterns of unsatisfactory results for conventional Pap smears and liquid‐based cytology: data from two randomised clinical trials. BJOG 2010;117:1067–1073.
Architectural modeling of a multi-tone/single-sideband serial link transceiver for lossy wireline data links

This paper presents a serial link transceiver (TRX) architecture that enables high-speed data transmission over a lossy backplane channel without the presence of equalization circuits. The proposed architecture employs multi-tone signaling to reduce inter-symbol interference (ISI) and to increase receiver (RX) timing margin. A single-sideband (SSB) modulation has also been employed for saving of required bandwidth per sub-channel, so as to minimize inter-channel interference (ICI). System-level simulation results show that the proposed TRX can easily transmit 20 Gb/s data stream over a lossy backplane channel that exhibits 28-dB attenuation at 10 GHz while requiring neither of continuous-time linear equalizer (CTLE) and decision feedback equalizer (DFE). By transmitting 3-to-5 Gb/s data stream over each of four sub-channels, at least 44% unit interval (UI) eye openings are achieved for all sub-channels when 20 Gb/s aggregate data is transmitted.
Sphingolipid-enriched Membrane Domains from Rat Cerebellar Granule Cells Differentiated in Culture

Sphingolipid-enriched membrane domains, characterized by a particular protein and lipid composition, have been detected in a variety of cells. However, limited data are available concerning these domains in neuronal cells. We analyzed the lipid and protein composition of a sphingolipid-enriched membrane fraction prepared from primary rat cerebellar granule cells differentiated in culture. Although the protein content of this fraction was only 1.4% of total cellular protein, 60% of the gangliosides, 67% of the sphingomyelin, 50% of the ceramide, and 40% of the cholesterol were located in this fraction. The protein pattern of the sphingolipid-enriched domain fraction was dramatically different from that associated with the cell homogenate. This fraction contained 25% of the tyrosine-phosphorylated proteins and was enriched in two proteins with apparent molecular masses of 135 and 15 kDa. 12% of cellular glycerophospholipids were located in the fraction, with phosphatidylcholine having the highest enrichment. The molar ratio between proteins, glycerophospholipids, cholesterol, sphingomyelin,ceramide and gangliosides in cerebellar granule cells was 1.6:41.6:6.1:1.3:0.3:1 in the cell homogenate and 0.04:8.3:4.0:1.4:0.2:1 in the sphingolipid-enriched membrane fraction. These data indicate that selected proteins segregate with sphingolipids in specialized domains in the membrane of cultured neurons.
Determinants of livelihood in the era of widespread access to ART

ABSTRACT We have only just begun to understand the long-term impact of living with chronic HIV on health and livelihood after a decade of widespread access to treatment in southern Africa. This paper explores health and well-being, disability, and livelihood dynamics among people living with HIV (PLHIV) in a public healthcare setting in South Africa. We undertook a cross-sectional survey among a cohort of 1042 people on ART and explored associations between socio-demographic characteristics, treatment adherence, measures of disability (functional and activity limitations), livelihood resources (capitals) and outcomes, including food security, and exposure to livelihood shocks. A range of dynamic relationships relevant for decision-makers is evident. Age, gender, and marital status all had significant associations with levels of livelihood capitals and outcomes. Those who had been on ART for longer periods of time also had significantly higher aggregate livelihood capital. This was particularly driven by social and financial capital. Livelihoods are built within specific social and health contexts. Of particular importance is that the resources drawn on to build a livelihood differ significantly between men and women, and that different forms of disability also have gender-specific pathways in influencing livelihood and livelihood outcomes. Our results support the need for a gender-sensitive approach to supporting the well-being and livelihoods of PLHIV. Of equal importance is an approach that considers more comprehensively the new experiences of comorbidities and disabilities that may occur with a long life on ART.
Approaches to combat with confounding by indication in observational studies of intended drug effects

There has been a resurgence of controversy about the usefulness of observational data to study the efficacy of drugs. Nearly every week a researcher makes some criticism of clinical trials or justifies observational research into intended effects, with other researchers offering a contradictory viewpoint. Literature reviews are not useful in this regard because the contradictory studies will not usually be carried out. Some methods are discussed which may have potential utility in the study of intended effects. There may be a marginal role for statistical techniques such as propensity scores and confounder scores. More promising techniques may include ecological analyses, restriction of subjects and blinded prospective review. Because it is currently unknown when the observational study of drug efficacy is possible, we should arguably always carry out a study of the determinants of prescribing first, and possibly consider using the various techniques that are outlined in this article. Copyright © 2003 John Wiley & Sons, Ltd.
Radiomic Phenotyping in Brain Cancer to Unravel Hidden Information in Medical Images

Abstract Radiomics is a new area of research in the field of imaging with tremendous potential to unravel the hidden information in digital images. The scope of radiology has grown exponentially over the last two decades; since the advent of radiomics, many quantitative imaging features can now be extracted from medical images through high-throughput computing, and these can be converted into mineable data that can help in linking imaging phenotypes with clinical data, genomics, proteomics, and other “omics” information. In cancer, radiomic imaging analysis aims at extracting imaging features embedded in the imaging data, which can act as a guide in the disease or cancer diagnosis, staging and planning interventions for treating patients, monitor patients on therapy, predict treatment response, and determine patient outcomes.