Miracle-dz/UniFAR-FTUs huggingface dataset:
Family history of stroke – a useful clue for the primary care physician and stroke neurologist: a narrative review

Purpose The heritability of ischemic stroke is a complex mechanism, involving the contribution of genetic traits and environmental factors, which is why in everyday practice clinicians often rely on the broad term “family history of stroke”, defined as the case of any first-degree relative who has had a stroke. The aim of this review is to update the available data regarding family history of stroke in primary and secondary stroke prevention by searching the electronic Scopus database for the phrase TITLE-ABS-KEY (“family history” AND “stroke”). Views A total of 140 articles met the pre-specified criteria and were included in the review. The prevalence of family history of stroke ranged from 37% in stroke-free individuals to 52% in patients with ischemic stroke. In primary prevention, family history of stroke was associated with increased risk of stroke, transient ischemic attack, stroke risk factors and stroke-like symptoms. In patients with ischemic stroke, it was more often associated with small- and large-vessel disease, though not with a cardioembolic etiology. Family history of stroke did not influence long-term functional outcomes after rehabilitation. In young stroke victims, it was related to symptom severity and the risk of a second stroke. Conclusions Consideration of family history of stroke in everyday practice may carry useful information both for primary care physicians and stroke neurologists.
Comparative Investigation of XPS Spectra of Oxidated Carbon Nanotubes and Graphene

X-ray photoelectron emission spectra of thermally reduced graphene oxide samples and carbon nanotubes (CNTs) with various oxidation degrees are presented in this paper. A method for the reconstruction of differential electron inelastic scattering cross sections from the energy loss spectra of photoelectrons is described and discussed. The analysis of the part of the characteristic photoelectron energy loss spectrum adjacent to the C1 peak indicated a considerable influence of the thermal reduction of graphene oxide on the electron properties of the samples obtained. On the contrary, the oxidation of CNTs by refluxing in a concentrated HNO3 solution does not change the free electron excitation spectrum.
Lasso-Based Machine Learning Algorithm for Predicting Postoperative Lung Complications in Elderly: A Single-Center Retrospective Study from China

Background The predictive effect of systemic inflammatory factors on postoperative pulmonary complications in elderly patients remains unclear. In addition, machine learning models are rarely used in prediction models for elderly patients. Patients and Methods We retrospectively evaluated elderly patients who underwent general anesthesia during a 6-year period. Eligible patients were randomly assigned in a 7:3 ratio to the development group and validation group. The Least logistic absolute shrinkage and selection operator (LASSO) regression model and multiple logistic regression analysis were used to select the optimal feature. The discrimination, calibration and net reclassification improvement (NRI) of the final model were compared with “the Assess Respiratory Risk in Surgical Patients in Catalonia” (ARISCAT) model. Results Of the 9775 patients analyzed, 8.31% developed PPCs. The final model included age, preoperative SpO2, ANS (the Albumin/NLR Score), operation time, and red blood cells (RBC) transfusion. The concordance index (C-index) values of the model for the development cohort and the validation cohort were 0.740 and 0.748, respectively. The P values of the Hosmer–Lemeshow test in two cohorts were insignificant. Our model outperformed ARISCAT model, with C-index (0.740 VS 0.717, P = 0.003) and NRI (0.117, P < 0.001). Conclusion Based on LASSO machine learning algorithm, we constructed a prediction model superior to ARISCAT model in predicting the risk of PPCs. Clinicians could utilize these predictors to optimize prospective and preventive interventions in this patient population.
Multivariate Entropy Analysis of Network Data

Multigraphs with numerical or qualitative attributes defined on vertices and edges can benefit from systematic methods based on multivariate entropies for describing and analysing the interdependencies that are present between vertex and edge attributes. This is here illustrated by application of these tools to a subset of data on the social relations among Renaissance Florentine families collected by John Padgett. Using multivariate entropies we show how it is possible to systematically check for tendencies in data that can be described as independencies or conditional independencies, or as dependencies allowing certain combinations of variables to predict other variables. We also show how different structural models can be tested by divergence measures obtained from the multivariate entropies.
Asymptotic solutions for turbulent mass transfer at high Schmidt number

We present closed-form solutions for high Schmidt number mass transfer in a hydrodynamically fully developed turbulent flow. Governing equations for the near- and far-field are developed for a large class of boundary conditions (BCs) for which the mass flux is a function of the concentration at the wall. We show that for this class of BCs, which includes nonlinear wall reactions, the mass transfer coefficient is independent of the BC and the Sherwood correlation is therefore universal. For Dirichlet, Neumann and Robin BCs, the far-field solutions are in good correspondence with the method of separating variables and near-field solutions are in good agreement with numerical simulations. However, in contrast with the far-field solutions, the Sherwood correlation in the near-field depends on the specific BC. As an example of nonlinear BCs, solutions for a second-order wall reaction are derived which are compared with numerical simulations and found to be in excellent agreement.
CAT-CapsNet: A Convolutional and Attention Based Capsule Network to Detect the Driver’s Distraction

Worldwide inflation in the count of road accidents has raised an alarming scenario wherein driver distraction is identified as one of the main causes. According to the National Highway Traffic Safety Administration survey, talking over the mobile or fellow passengers, eating or drinking while driving, and operating in-vehicle menus can lead to distract the driver. Therefore, this paper presents a new driver distraction detection method to cater such scenarios. The proposed method is a convolution-based capsule network with attention mechanism, termed as CAT-CapsNet, that combines the computation capabilities of capsule network with attention module and convolution filters. We evaluate the proposed CAT-CapsNet on two publicly available driver distraction datasets namely, American University in Cairo (AUC) distracted driver dataset and Statefarmŝ dataset. A comparative analysis of the proposed model is conducted against 16 (approx) state-of-the-art methods in terms of accuracy, number of parameters, and AUC curves. Experiments affirm that CAT-CapsNet outperforms with the accuracy of 99.88% on SFD dataset and 96.7% accuracy on the AUC dataset. Moreover, the proposed model has only $8.5M$ parameters to train and no data augmentation is needed in-case training samples are less.
Strahlenexposition des Personals im Herzkatheterlabor

Zusammenfassung Die Strahlenexposition des Personals im Herzkatheterlabor wird auf der Basis von Messungen der Ortsdosisleistung wahrend Patientenuntersuchungen ermittelt. Dabei werden Werte in verschiedenen Hohen an reprasentativen Aufenthaltsorten mit und ohne Dauerschutzeinrichtungen bestimmt. Zur Bestimmung der effektiven Dosen werden TLD-Messungen mit einem Alderson-Phantom als Streukorper und einem zweiten als Untersucher durchgefuhrt. Unterschiedliche Ausfuhrungen von personlichen Schutzausrustungen und die Auswirkungen der Dauerschutzeinrichtungen werden rechnerisch einbezogen. Es wird gezeigt, dass einerseits unter optimierten Bedingungen ein guter Strahlenschutz mit effektiven Dosen unter 1 mSv/Jahr realisiert werden kann, andererseits aber Mangel in der Schutzausrustung zu erheblichen Dosiserhohungen fuhren. Allein das Fehlen eines Schilddrusenschutzes bewirkt eine Erhohung der effektiven Dosis des Untersuchers um einen Faktor 3. Fur alle Aufenthaltsorte unterschatzt die Tiefen-Personendosis Hp(10) (amtliche Personendosis) systematisch die effektive Dosis; der entsprechende Faktor betragt je nach der speziellen Strahlenschutzsituation zwischen 1,5 und 4,8.
Do market incentives for hospitals affect health and service utilization?: evidence from prospective pay system–diagnosis‐related groups tariffs in Italian regions

We exploit variation across Italian regions in the implementation of region‐specific tariffs within a prospective pay system for hospitals based on diagnosis‐related groups to assess their effect on health and on the use of healthcare services. We consider survey data for the years 1993–2007 with information on both individuals’ perceived health and their utilization of healthcare services. The results suggest that the introduction of market incentives via a fixed price payment system did not lead to worse health perceptions. Instead, it marked a moderate decrease in hospitalization coupled with a clearer decrease in the utilization of emergency services. We also find mild evidence of reduced satisfaction with healthcare services among hospital patients. These effects were stronger for adoptions occurring when also the national government supported the market‐based approach. Results are robust to sensitivity checks.
Updates of precision medicine in type 2 diabetes

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors recently, the proportion of patients achieving satisfactory glucose control has not risen as expected. The heterogeneity of diabetes determines that a one-size-fits-all strategy is not suitable for people with diabetes. Diabetes is undoubtedly more heterogeneous than the conventional subclassification, such as type 1, type 2, monogenic and gestational diabetes. The recent progress in genetics and epigenetics of diabetes has gradually unveiled the mechanisms underlying the heterogeneity of diabetes, and cluster analysis has shown promising results in the substratification of type 2 diabetes, which accounts for 95% of diabetic patients. More recently, the rapid development of sophisticated glucose monitoring and artificial intelligence technologies further enabled comprehensive consideration of the complex individual genetic and clinical information and might ultimately realize a precision diagnosis and treatment in diabetics.
The Association of Planetary Health Diet with the Risk of Type 2 Diabetes and Related Complications: A Systematic Review

Background: Nutritional interventions such as the planetary health diet, which the EAT-Lancet commission proposed, may be an effective strategy for reducing type 2 diabetes risks and its associated complications. The planetary health diet demonstrates the significant role of diet in associating human health with environmental sustainability and the significance of transforming food systems in order to ensure that the UN’s Sustainable Development Goals and the Paris Agreement are achieved. Therefore, the aim of this review is to examine the association of the planetary health diet (PHD) with the risk of type 2 diabetes and its related complications. Method: The systematic review was conducted in line with established guidelines. The searches were carried out in health sciences research databases through EBSCOHost. The population, intervention, comparator and outcomes framework was used in order to define the research question and the search terms. The searches were carried out from the inception of the databases to 15 November 2022. Search terms including synonyms and medical subject headings were combined using Boolean operators (OR/AND). Results: Seven studies were included in the review and four themes were identified, including incidence of diabetes; cardiovascular risk factors and other disease risks; indicators of obesity and indicators of environmental sustainability. Two studies examined the association between the PHD and the incidence of type 2 diabetes and found that high adherence to the reference diet (EAT-Lancet reference diet) was correlated with a lower incidence of type 2 diabetes. High adherence to the PHD was also associated with some cardiovascular risk factors and environmental sustainability. Conclusion: This systematic review has shown that high adherence to the PHD is associated with a reduced risk of type 2 diabetes and may be associated with a lower risk of subarachnoid stroke. In addition, an inverse relationship was found between adherence to the PHD and markers of obesity and environmental sustainability. Adherence to the reference diet was also associated with lower values of some markers of cardiovascular risk. More studies are needed to fully examine the relationship between the planetary health diet, type 2 diabetes and its related conditions.
Assessment of Treatment Outcome and Its Associated Factors among Adult Epileptic Patients in Public Hospitals in the Southern Ethiopia: A Multi-center Cross-sectional Study

Background Epilepsy accounts for 0.5 % of the world's disease burden. Around 80 % of these are living in low and middle-income countries. In Ethiopia, the prevalence is 0.6 to 5 per 1000 population. There is a little study in our study area on the treatment and predictors of response of adult epilepsy. The purpose of this study was to determine the treatment outcome and its associated factors among adult epileptic patients in public hospitals in southern Ethiopia. Methods Multi-centered, Hospital-based cross-sectional study was conducted from October 2021 - august 2022. Data were collected by face-to-face interviews and record review. Data was analysed using SPSS. The bivariate and multivariable logistic regression analyses have been performed between the dependent and the independent variables. Result Of the total 422 participants, 55.9 % were males and 62.6% were below 30 years of age. The most common type of seizure was a generalized tonic-clonic seizure. Most (87.9 %) were treated by immunotherapy. Phenobarbitone is most common medication (77.5). One-quarter reported adverse effects of medication. The majority (78%) had good control (seizure free for at least one year) and 22% had poor control. Poor medication adherence (AOR=4.03) and shorter duration of seizure before treatment (AOR=4.233) were associated with poor control. Conclusion A significant number of patients had poor control of seizures. Early identification of issues on medication adherence and early initiation of treatment will improve treatment outcome.
Volume and aboveground biomass models for a dry evergreen montane forest in Tanzania

Abstract. Mwaluseke ML, Mwakalukwa EE, Maliondo SMS. 2023. Volume and aboveground biomass models for a dry evergreen montane forest in Tanzania. Asian J For 7: 45-53. Models available for accurately estimating trees and shrubs' volume and aboveground biomass from dry evergreen montane forests in Tanzania are largely lacking. Therefore, this study was conducted to develop volume, and aboveground biomass models for a dry evergreen montane forest of Lendikinya Forest Reserve found in Northern Tanzania. A total of thirty sample trees and shrubs with a diameter range of 5-58.5 cm were destructively harvested and used in this study. Specifically, the study developed (i) the height-diameter model and (ii) the total volume and aboveground biomass models. The following height, volume, and biomass models appear to be suitable for estimating tree height, volume, and biomass of tree and shrub species found in the study site: Height (m) =2.3249 + 6.6101/DBH + 0.2847DBH (R2 = 0.78, RMSE = 1.79, AIC = 164.37), ln(Volume, m3) = -9.845 + 1.915 ln(DBH) + 1.089ln(Ht) (R2 = 0.97, RMSE = 0.296, AIC = -144.18) and ln(Biomass, kg) = -1.666 + 0.853ln(WD x DBH2 x Ht) (R2 = 0.95, RMSE = 0.324, AIC = 224.13). Both models yielded low bias, hence indicating an excellent fit. These models will be useful in understanding the condition of the forest and the potential of this forest in storing carbon hence, the possibility of benefiting from the ongoing negotiations of REDD+ schemes for payment for avoided deforestation and degradation through sustainable management of the reserve.
Low Multiplication Noise Thin Avalanche Photodiodes

Abstract— Avalanche multiplication and excess noise weremeasured on a series of Al 0 6 Ga 0 4 As p + in + and n + ip + diodes,with avalanche region thickness, ranging from 0.026 m to 0.85m. The results show that the ionization coefficient for electronsis slightly higher than for holes in thick, bulk material. At fixedmultiplication values the excess noise factor was found to decreasewith decreasing , irrespective of injected carrier type. Owingto the wide Al 0 6 Ga 0 4 As bandgap extremely thin devices cansustain very high electric fields, giving rise to very low excess noisefactors, of around 3.3 at a multiplication factor of 15.5in the structure with = 0.026 m. This is the lowest reportedexcess noise at this value of multiplication for devices grown onGaAs substrates. Recursion equation modeling, using both ahard threshold dead space model and one which incorporatesthe detailed history of the ionizing carriers, is used to model thenonlocal nature of impact ionization giving rise to the reductionin excess noise with decreasing . Although the hard thresholddead space model could reproduce qualitatively the experimentalresults better agreement was obtained from the history-dependentmodel.Index Terms— Al Ga
Overview of the field phase of the fronts and Atlantic Storm‐Track EXperiment (FASTEX) project

The field phase of the Fronts and Atlantic Storm‐Track Experiment (FASTEX) project took place between 5 January and 27 February 1997 with the deployment of a unique set of observing facilities across the North Atlantic. the major objective was to document the life cycle of a representative set of mid‐latitude cyclones. Other objectives were to test the practical feasibility of ‘adaptive’ observations with a view to improving the prediction of these same cyclones and to document the internal structure of the associated cloud systems using combined airborne Doppler radars and dropsondes. Another goal of FASTEX was to measure air‐sea exchange parameters under conditions of strong winds with high seas.
A Novel Robust Watermarking Algorithm Based on DWT and DCT

In this paper, a novel robust watermarking algorithm is presented in mixed transform domain. The original host image is first decomposed into four sub-bands by Discrete Wavelet Transform (DWT). Then approximate coefficients are relocated by Arnold transform to create a noise-like version and divided into non-overlapping 8×8 blocks. Each block is Zig-zag scanned and sorted in descending order before the DCT transform to obtain high robustness and transparency. A watermarking sequence encrypted by Arnold transformation with secret keys is afterwards embedded into the DCT transform coefficients according to JND (Just Noticeable Difference) model. The watermark is extracted without the original image. Experimental results indicate that the proposed strategy has a good robustness against common attacks, such as noise, filtering, JPEG compression.
Using Machine Learning Methods in Identifying Genes Associated with COVID-19 in Cardiomyocytes and Cardiac Vascular Endothelial Cells

Corona Virus Disease 2019 (COVID-19) not only causes respiratory system damage, but also imposes strain on the cardiovascular system. Vascular endothelial cells and cardiomyocytes play an important role in cardiac function. The aberrant expression of genes in vascular endothelial cells and cardiomyocytes can lead to cardiovascular diseases. In this study, we sought to explain the influence of respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the gene expression levels of vascular endothelial cells and cardiomyocytes. We designed an advanced machine learning-based workflow to analyze the gene expression profile data of vascular endothelial cells and cardiomyocytes from patients with COVID-19 and healthy controls. An incremental feature selection method with a decision tree was used in building efficient classifiers and summarizing quantitative classification genes and rules. Some key genes, such as MALAT1, MT-CO1, and CD36, were extracted, which exert important effects on cardiac function, from the gene expression matrix of 104,182 cardiomyocytes, including 12,007 cells from patients with COVID-19 and 92,175 cells from healthy controls, and 22,438 vascular endothelial cells, including 10,812 cells from patients with COVID-19 and 11,626 cells from healthy controls. The findings reported in this study may provide insights into the effect of COVID-19 on cardiac cells and further explain the pathogenesis of COVID-19, and they may facilitate the identification of potential therapeutic targets.
Exploiting Cooperative Downlink NOMA in D2D Communications

We propose and investigate a bidirectional device-to-device (D2D) transmission scheme that exploits cooperative downlink non-orthogonal multiple access (NOMA) (termed as BCD-NOMA). In BCD-NOMA, two source nodes communicate with their corresponding destination nodes via a relaying node while exchanging bidirectional D2D messages simultaneously. BCD-NOMA is designed for improved outage probability (OP) performance, high ergodic capacity (EC) and high energy efficiency by allowing two sources to share the same relaying node for data transmission to their corresponding destination nodes while also facilitating bidirectional D2D communications exploiting downlink NOMA. Simulation and analytical expressions of the OP, EC and ergodic sum capacity (ESC) under both perfect and imperfect successive interference cancellation (SIC) are used to demonstrate the effectiveness of BCD-NOMA compared to conventional schemes.
Temporal Aggregation and Bandwidth selection in estimating long memory

This article aims at showing that a temporal aggregation and a specific bandwidth reduction lead to the same asymptotic properties in estimating long memory by Geweke and Porter‐Hudak's [Journal of Time Series Analysis (1983 ) vol. 4, pp. 221–237] and Robinson's [Annals of Statistics (1995b ) vol. 23, pp. 1630–1661] estimators. In other words, irrespective of the level of temporal aggregation, the asymptotic properties of the estimator are uniquely determined by the number of periodogram ordinates used in the estimation, provided some mild additional assumptions are imposed. Monte Carlo simulations show that this result is a good approximation in finite samples. A real example with the daily US Dollar/French Franc exchange rate series is also provided.
GAMBARAN KONSUMSI SUPLEMEN DAN HERBAL PADA MAHASISWA SEBELUM DAN SELAMA PANDEMI COVID-19

Daya tahan tubuh yang kuat merupakan salah satu kunci terhindar dari infeksi virus COVID-19. Selain makanan bergizi, asupan suplemen dan minuman herbal juga diyakini dapat meningkatkan daya tahan tubuh seseorang. Penelitian ini bertujuan untuk melihat gambaran asupan konsumsi suplemen dan herbal pada mahasiswa sebelum dan selama pandemi COVID-19. Penelitian ini menggunakan desain observasional dan metode potong lintang dengan menyebarkan kuesioner online via google form pada mahasiswa di Indonesia. Pengisian kuisioner online dibuka pada bulan September hingga Oktober 2020. Pemilihan subjek pada penelitian ini dilakukan secara non random sampling yaitu mahasiswa perguruan tinggi di Indonesia, berusia 18-25 tahun, bersedia mengikuti penelitian dan menyelesaikan pengisian kuesioner, Sebanyak 3.024 subjek berpatisipasi. Hasil penelitian menunjukan asal daerah berhubungan erat dengan konsumsi suplemen dan herbal sebelum dan selama pandemi COVID -19 (p value <0,05), sedangkan rumpun ilmu berhubungan erat dengan konsumsi suplemen selama masa pandemi COVID -19 (p value 0,026).