bluuebunny/crossref_metadata_2025_split huggingface dataset:
Breast cancer recognition based on performance evaluation of machine learning algorithms
Authors: Haydar Salih Chiman , M. Ali Abbas 
Published: July 2022

Breast cancer is the one common cause of death in both developed worlds and the most death-causing disease diagnosed among women. <span lang="EN-US">Early recognition of this condition can help to minimize death rates. The breast problem statement, in brief, is not reliable for accuracy recognition. They have a high degree of classification accuracy as well as diagnostic capabilities. The most common classifications are normal, benign cancer, and malignant cancer. Machine learning (ML) techniques are now widely used in the classification of breast cancer. In this paper, some machine learning technics have been investigated to diagnose breast cancer (BC) on magnetic resonance imaging (MRI) images using multi-step processes. The first step has been to take the MRI image as an input image and have been pre-processing an image, then use feature extraction by using (scale-invariant feature transform (SIFT), histogram of oriented gradient (HOG), local binary patterns (LBP), bag of words (BoW), and edge-oriented histogram (EOH)). Next step we implement the classifying algorithms (KNN, decision tree (DT), naïve Bayes, ANN, SVM, RF, AdaBoost), have been used to detect and classify the normal or breast cancer region for this purpose datasets like ACRIN-Contralateral-Breast-MRI, In and breast cancer MRI dataset) has been collected our breast cancer MRI images from Erbil and Sulaymaniyah hospital the results was 91.9%, the result of ACRIN was 97% and the results Breast Cancer was 92.3%.</span>
Trends in Uptake and Adherence to Oral Anticoagulation for Patients With Incident Atrial Fibrillation at High Stroke Risk Across Health Care Settings
Authors: Yogasundaram Haran , Dover Douglas C. , Hawkins Nathaniel M. , McAlister Finlay A. , Goodman Shaun G. , Ezekowitz Justin , Kaul Padma , Sandhu Roopinder K. 
Published: July 2022

Background
Oral anticoagulation (OAC) therapy prevents morbidity and mortality in nonvalvular atrial fibrillation; whether location of diagnosis influences OAC uptake or adherence is unknown.

Methods and Results

Retrospective cohort study (2008–2019), identifying adults with incident nonvalvular atrial fibrillation across health care settings (emergency department, hospital, outpatient) at high risk of stroke. OAC uptake and adherence via proportion of days covered for direct OACs and time in therapeutic range for warfarin were measured. Proportion of days covered was categorized as low (0–39%), intermediate (40–79%), and high (80–100%). Warfarin control was defined as time in therapeutic range ≥65%. All‐cause mortality was examined at a 3‐year landmark. Among 75 389 patients with nonvalvular atrial fibrillation (47.0% women, mean 77.4 years), 19.7% were diagnosed in the emergency department, 59.1% in the hospital, and 21.2% in the outpatient setting. Ninety‐day OAC uptake was 51.6% in the emergency department, 50.9% in the hospital, and 67.9% in the outpatient setting (
P
<0.0001). High direct OAC adherence increased from 64.9% to 80.3% in the emergency department, 64.3% to 81.7% in the hospital, and 70.9% to 88.6% in the outpatient setting over time (
P
values for trend <0.0001). Warfarin control was 40.3% overall and remained unchanged. In multivariable analysis, outpatient diagnosis compared with the hospital was associated with greater OAC uptake (odds ratio [OR], 1.79; [95% CI, 1.72–1.87]) and direct OAC (OR, 1.42; [95% CI, 1.27–1.59]) and warfarin (OR, 1.49; [95% CI, 1.36–1.63]) adherence. Varying or persistently low adherence was associated with a poor prognosis, especially for warfarin.

Conclusions
Locale of nonvalvular atrial fibrillation diagnosis is associated with varying OAC uptake and adherence. Interventions specific to health care settings are needed to improve stroke prevention.
Fibroblast Growth Factor 23 and Risk of New Onset Heart Failure With Preserved or Reduced Ejection Fraction: The PREVEND Study
Authors: Binnenmars S. Heleen , Hoogslag Georgette E. , Yeung Stanley M. H. , Brouwers Frank P. , Bakker Stephan J. L. , van Gilst Wiek H. , Gansevoort Ron T. , Navis Gerjan , Voors Adriaan A. , de Borst Martin H. 
Published: July 2022

Background
The role of fibroblast growth factor 23 (FGF23) in the development of new‐onset heart failure (HF) with reduced (HFrEF) or preserved ejection fraction (HFpEF) in the general population is unknown. Therefore, we set out to investigate associations of C‐terminal FGF23 with development of new‐onset HF and, more specifically, with HFrEF or HFpEF in a large, prospective, population‐based cohort.

Methods and Results

We studied 6830 participants (aged 53.8±12.1 years; 49.7% men; estimated glomerular filtration rate, 93.1±15.7 mL/min per 1.73 m
2
) in the community‐based PREVEND (Prevention of Renal and Vascular End‐Stage Disease) study who were free of HF at baseline. Cross‐sectional multivariable linear regression analysis showed that ferritin (standardized β, −0.24;
P
<0.001) and estimated glomerular filtration rate (standardized β, −0.13;
P
<0.001) were the strongest independent correlates of FGF23. Multivariable Cox proportional hazard regression was used to study the association between baseline FGF23 and incident HF, HFrEF (ejection fraction ≤40%) or HFpEF (ejection fraction ≥50%). After median follow‐up of 7.4 [IQR 6.9–7.9] years, 227 individuals (3.3%) developed new‐onset HF, of whom 132 had HFrEF and 88 had HFpEF. A higher FGF23 level was associated with an increased risk of incident HF (fully adjusted hazard ratio, 1.29 [95% CI, 1.06–1.57]) and with an increased risk of incident HFrEF (fully adjusted hazard ratio, 1.31 [95% CI, 1.01–1.69]). The association between FGF23 and incident HFpEF lost statistical significance after multivariable adjustment (hazard ratio, 1.22 [95% CI, 0.87–1.71]).

Conclusions
Higher FGF23 is independently associated with new‐onset HFrEF in analyses fully adjusted for cardiovascular risk factors and other potential confounders. The association between FGF23 and incident HFpEF lost statistical significance upon multivariable adjustment.
RNF213
R4810K Variant in Suspected Unilateral Moyamoya Disease Predicts Contralateral Progression
Authors: Ok Taedong , Jung Yo Han , Kim Jinkwon , Park Sang Kyu , Park Goeun , Lee Sujee , Lee Kyung‐Yul 
Published: July 2022

Background
Early‐stage unilateral moyamoya disease (MMD) is difficult to discriminate from isolated intracranial atherosclerotic stenosis, and identification of contralateral progression may aid in the diagnosis of MMD. The RNF213 (ring finger protein 213) R4810K variant is a strong genetic susceptibility factor for MMD; however, the role of contralateral progression in unilateral MMD is unknown.

Methods and Results

Patients who had undergone
RNF213
R4810K genotyping with suspected unilateral MMD between January 2017 and August 2021 from 2 tertiary university hospitals were retrospectively reviewed. We compared the clinical features and radiographic outcomes of patients with and without this variant. The risk factors of contralateral progression in patients with suspected unilateral MMD were evaluated. The
RNF213
R4810K variant was observed in 72 of 123 patients with suspected unilateral MMD, all of which were heterozygous. The allele frequency of the R4810K variant was significantly higher in the suspected unilateral MMD group compared with the historical control group (29.3% versus 1.2%;
P
<0.0001). Family history of MMD was significantly more common in patients with the variant than in those without (17% versus 4%;
P
=0.003). Eleven of 72 patients with the variant developed contralateral progression, whereas only 1 of 51 patients without the variant developed contralateral progression during a median follow‐up period of 28 months (log‐rank test;
P
=0.03). The presence of the
RNF213
R4810K variant significantly correlated with contralateral progression (adjusted odds ratio, 6.39 [95% CI, 1.11–36.63];
P
=0.04).

Conclusions

Contralateral progression is more likely to occur in patients with suspected unilateral MMD with the
RNF213
R4810K variant than in those without the variant. However, because our study used a small sample size, this finding should be carefully interpreted and requires further studies with more patients and longer follow‐up periods.
Estimating Perfusion Deficits in Acute Stroke Patients Without Perfusion Imaging
Authors: Reyes Dennys , Simpkins Alexis N. , Hitomi Emi , Lynch John K. , Hsia Amie W. , Nadareishvili Zurab , Luby Marie , Latour Lawrence L. , Leigh Richard 
Published: July 2022

Background:
Perfusion weighted imaging (PWI) is critical for determining whether stroke patients presenting in an extended time window are candidates for mechanical thrombectomy. However, PWI is not always available. Fluid-attenuated inversion recovery hyperintense vessels (FHVs) are seen in patients with a PWI lesion. We investigated whether a scale measuring the extent FHV could serve as a surrogate for PWI to determine eligibility for thrombectomy.

Methods:
The National Institutes of Health (NIH) FHV score was developed to quantify the burden of FHV and applied to magnetic resonance imaging scans of stroke patients with fluid-attenuated inversion recovery and perfusion imaging. The NIH-FHV was combined with the diffusion weighted image volume to estimate the diffusion-perfusion mismatch ratio. Linear regression was used to compare PWI volumes and mismatch ratios with estimates from the NIH-FHV score. Receiver operating characteristic analysis was used to test the ability of the NIH-FHV score to identify a significant mismatch.

Results:

There were 101 patients included in the analysis, of whom 78% had a perfusion deficit detected on PWI with a mean lesion volume of 47 (±59) mL. The NIH-FHV score was strongly associated with the PWI lesion volume (
P
<0.001; R
2
=0.32; β-coefficient, 0.57). When combined with diffusion weighted image lesion volume, receiver operating characteristic analysis testing the ability to detect a mismatch ratio ≥1.8 using the NIH-FHV score resulted in an area under the curve of 0.94.

Conclusions:
The NIH-FHV score provides an estimate of the PWI lesion volume and, when combined with diffusion weighted imaging, may be helpful when trying to determine whether there is a clinically relevant diffusion-perfusion mismatch in situations where perfusion imaging is not available. Further studies are needed to validate this approach.
Theoretical foundations of studying criticality in the brain
Authors: Tian Yang , Tan Zeren , Hou Hedong , Li Guoqi , Cheng Aohua , Qiu Yike , Weng Kangyu , Chen Chun , Sun Pei 
Published: July 2022

Abstract
Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information-processing capacities in the brain. While considerable evidence generally supports this hypothesis, nonnegligible controversies persist regarding the ubiquity of criticality in neural dynamics and its role in information processing. Validity issues frequently arise during identifying potential brain criticality from empirical data. Moreover, the functional benefits implied by brain criticality are frequently misconceived or unduly generalized. These problems stem from the nontriviality and immaturity of the physical theories that analytically derive brain criticality and the statistic techniques that estimate brain criticality from empirical data. To help solve these problems, we present a systematic review and reformulate the foundations of studying brain criticality, that is, ordinary criticality (OC), quasi-criticality (qC), self-organized criticality (SOC), and self-organized quasi-criticality (SOqC), using the terminology of neuroscience. We offer accessible explanations of the physical theories and statistical techniques of brain criticality, providing step-by-step derivations to characterize neural dynamics as a physical system with avalanches. We summarize error-prone details and existing limitations in brain criticality analysis and suggest possible solutions. Moreover, we present a forward-looking perspective on how optimizing the foundations of studying brain criticality can deepen our understanding of various neuroscience questions.
Dynamical interactions reconfigure the gradient of cortical timescales
Authors: Sorrentino P. , Rabuffo G. , Baselice F. , Troisi Lopez E. , Liparoti M. , Quarantelli M. , Sorrentino G. , Bernard C. , Jirsa V. 
Published: July 2022

Abstract
The functional organization of the brain is usually presented with a back-to-front gradient of timescales, reflecting regional specialization with sensory areas (back) processing information faster than associative areas (front), which perform information integration. However, cognitive processes require not only local information processing but also coordinated activity across regions. Using magnetoencephalography recordings, we find that the functional connectivity at the edge level (between two regions) is also characterized by a back-to-front gradient of timescales following that of the regional gradient. Unexpectedly, we demonstrate a reverse front-to-back gradient when nonlocal interactions are prominent. Thus, the timescales are dynamic and can switch between back-to-front and front-to-back patterns.
Feud, Law, and Society in Mid-Nineteenth-Century Northern Albania
Authors: Bayraktar Uğur 
Published: July 2022

Abstract
The present article investigates the kanun or Albanian “customary law”, with a particular focus on feuds in the town of Dibra. It explores a case of Ottoman legal pluralism in which the kanun and Ottoman law interacted, a major watershed in the development of Ottoman law. By shifting the perspective to the Albanian highlanders’ understanding of “law”, this paper sheds light on how a set of customary laws contributed to the making of the Tanzimat, which called for a standardised legal framework in the provinces. It examines the means the Ottoman government developed to eliminate feuds and demonstrates that the Tanzimat converged with the principles of Albanian customary law. Analysis of this interaction between the kanun and state law demonstrates how this process constituted one of the foundations of the modern Ottoman legal order in northern Albania.
Mitigating Climate Biases in the Midlatitude North Atlantic by Increasing Model Resolution: SST Gradients and Their Relation to Blocking and the Jet
Authors: Athanasiadis Panos J. , Ogawa Fumiaki , Omrani Nour-Eddine , Keenlyside Noel , Schiemann Reinhard , Baker Alexander J. , Vidale Pier Luigi , Bellucci Alessio , Ruggieri Paolo , Haarsma Rein , Roberts Malcolm , Roberts Chris , Novak Lenka , Gualdi Silvio 
Published: July 2022

Abstract
Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 1° to 0.25° in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multimodel ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multimodel ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the storm track. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate.
Soil Moisture and Streamflow Data Assimilation for Streamflow Prediction in the Narmada River Basin
Authors: Prakash Ved , Mishra Vimal 
Published: July 2022

Abstract
An accurate streamflow forecast is vital for flood prediction and early warning systems. Notwithstanding the rising frequency and intensity of floods during the summer monsoon season in India, efforts to examine the utility of data assimilation (DA) for streamflow prediction remain limited. We examine soil moisture and streamflow DA to improve streamflow simulations in the Narmada River basin, considered a testbed. Data assimilation was performed using the Variable Infiltration Capacity (VIC) model at four gauge stations in the basin. First, we used the ensemble Kalman filter (EnKF) to assimilate the satellite soil moisture from the European Space Agency Climate Change Initiative (ESA-CCI) to the initial state of the VIC model. We examined the usefulness of observed streamflow from the India Water Resources Information System (India-WRIS) to improve the initial hydrological conditions of the VIC model in the streamflow DA during the summer monsoon (June–September) season from 1980 to 2018. The assimilation of ESA-CCI soil moisture showed less improvement in percent error reduction (PER) and efficiency index (EFF) (less than 2%) than the streamflow DA at all of the four gauge locations in the Narmada basin. On the other hand, the streamflow DA showed a significant improvement in PER and EFF (more than 10%) at all the gauge stations for both mean and high-flow conditions. Streamflow data assimilation improved errors in the magnitude and timing for the major floods in 1994 and 2013.

Significance Statement
India is considerably affected by floods during the summer monsoon. Floods have increased and are projected to become more frequent under the warming climate. Flood prediction and early warning systems are essential in reducing their impacts and exposure. In the present study, we are interested in examining the role of soil moisture and streamflow data assimilation on flood prediction in the Narmada River basin. Our results show that streamflow data assimilation is more effective in reducing errors and bias in streamflow prediction than soil moisture data assimilation. The hydrologic framework used for the Narmada basin can be extended and evaluated to other flood-prone basins in India.
Variability of Heat Content and Eddy Kinetic Energy in the Southeast Indian Ocean: Roles of the Indonesian Throughflow and Local Wind Forcing
Authors: Li Yuanlong , Guo Yaru , Zhu Yanan , Kido Shoichiro , Zhang Lei , Wang Fan 
Published: July 2022

Abstract
Prominent interannual-to-decadal variations were observed in both heat content and mesoscale eddy activity in the southeast Indian Ocean (SEIO) during 1993–2020. The 2000–01 and 2008–14 periods stand out with increased 0–700-m ocean heat content (OHC) by ∼4.0 × 1021 J and enhanced surface eddy kinetic energy (EKE) by 12.5% over 85°–115°E, 35°–12°S. This study provides insights into the key dynamical processes conducive to these variations by analyzing observational datasets and high-resolution regional ocean model simulations. The strengthening of the Indonesian Throughflow (ITF) and anomalous cyclonic winds over the SEIO region during the two periods are demonstrated to be the most influential. While the ITF caused prevailing warming of the upper SEIO, the cyclonic winds cooled the South Equatorial Current and attenuated the warming in the subtropical SEIO by evoking upwelling Rossby waves. The EKE increase exerts significant influence on OHC only in the Leeuwin Current system. Dynamical instabilities of the Leeuwin Current give rise to high EKEs and westward eddy heat transport in climatology. As the Leeuwin Current was enhanced by both the ITF and local winds, the elevated EKEs drove anomalous heat convergence on its offshore flank. This process considerably contributes to the OHC increase in the subtropical SEIO and erases the wind-driven cooling during the two warm periods. This work highlights the vital role of eddies in regional heat redistribution, with implications for understanding time-varying ocean heat storage in a changing climate.
Performance Modeling of a Diode-Laser-Based Direct-Detection Doppler Lidar for Vertical Wind Profiling
Authors: Repasky Kevin S. , Cruikshank Owen , Colberg Luke 
Published: July 2022

Abstract
Micropulse differential absorption lidars (MPD) for water vapor, temperature, and aerosol profiling have been developed, demonstrated, and are addressing the needs of the atmospheric science community for low-cost ground-based networkable instruments capable of long-term monitoring of the lower troposphere. The MPD instruments use a diode-laser-based (DLB) architecture that can easily be adapted for a wide range of applications. In this study, a DLB direct-detection Doppler lidar based on the current MPD architecture is modeled to better understand the efficacy of the instrument for vertical wind velocity measurements, with the long-term goal of incorporating these measurements into the current network of MPD instruments. The direct-detection Doppler lidar is based on a double-edge receiver that utilizes two Fabry–Pérot interferometers and a vertical velocity retrieval that requires the ancillary measurement of the backscatter ratio, which is the ratio of the total backscatter coefficient to the molecular backscatter coefficient. The modeling in this paper accounts for the major sources of error. It indicates that the vertical velocity can be retrieved with an error of less than 0.56 m s−1 below 4 km with a 150-m range resolution and an averaging time of 5 min.

Significance Statement
Monitoring the temperature, relative humidity, and winds in the lower atmosphere is important for improving weather forecasting, particularly for severe weather such as thunderstorms. Cost-effective micropulse differential absorption lidar (MPD) instrumentation for continuous temperature and humidity monitoring has been developed and demonstrated, and its effects on weather forecasting are currently being evaluated. The modeling study described in this paper studies the feasibility of using a similar cost-effective MPD instrument architecture for monitoring vertical wind velocity in the lower atmosphere. Modeling indicates that wind velocities can be measured with less than 0.56 m s−1 accuracy and demonstrates the feasibility of adding vertical wind velocity measurements to the MPD instruments.