Miracle-dz/UniFAR-FTUs huggingface dataset:
Great doctors and scientists from the East: from princes of Persia, to icons of Asian science

Asian scholars especially from Iran and China preserved most of the wisdom and knowledge of antiquity in their writing and they had great influence even on both European traditional and modern medical sciences. The current searching was done by the keywords in main indexing systems including PubMed/MEDLINE, Scopus and Institute for Scientific Information Web of Science as well as the search engine of Google Scholar. Avicenna famous book was Canon, which reviewed all medical knowledge studied by the ancient Greek and Muslim scientists. Avicenna has introduced many medicinal plants and herbs and its knowledge influenced by both Eastern and Western traditional science. Rhazes was a great Persian alchemist, musician, mathematician, philosopher and physician. Bian Que was one of the most famous medical man and physician in ancient China who attached particular importance to the changes in the pulse examination. He is known as the founder of traditional Chinese medicine, and his four diagnostic methods were inspection, smelling and listening, inquiry, and palpation. Hua Tuo, Zhang Zhongjing, and Ge Hong were eclectic philosophers who dedicated his life to searching for physical immortality and traditional Chinese medicine, which he thought was attainable through alchemy. Sun Simiao also valued sanitation, exercise and disease prevention. Li Shizhen, a famous Chinese scholar who compiled a highly influential material medica. It is recommended to survey on their rules in different majors with details in future studies to make a better connection between modern and historical medical science.
Convolutional Neural Network With Adaptive Batch-Size Training Technique for High-Dimensional Inverse Modeling of Microwave Filters

This letter proposes a convolutional neural network (CNN) modeling technique with an adaptive batch-size training technique for high-dimensional inverse modeling of microwave filters. Real and imaginary parts of the $S$ -parameters are used as two-channel model inputs and coupling matrix of the filter is used as the model output. Since smooth activation function is needed for microwave modeling, the sigmoid function is introduced as the activation function in the proposed CNN. To further reduce the training time and increase the modeling accuracy, we propose an adaptive batch-size training strategy for developing the proposed CNN model. The proposed CNN inverse model with the adaptive batch size training strategy is demonstrated using two high-dimensional microwave filter examples.
Novel biomarkers for diabetic kidney disease

Although diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in patients with diabetes mellitus; its prevalence has failed to decline over the past 30 years. To identify those at high risk of developing DKD and disease progression at an early stage, extensive research has been ongoing in the search for prognostic and surrogate endpoint biomarkers for DKD. Although biomarkers are not used routinely in clinical practice or prospective clinical trials, many biomarkers have been developed to improve the early identification and prognostication of patients with DKD. Novel biomarkers that capture one specific mechanism of the DKD disease process have been developed, and studies have evaluated the prognostic value of assay-based biomarkers either in small sets or in combinations involving multiple biomarkers. More recently, several studies have assessed the prognostic value of omics-based biomarkers that include proteomics, metabolomics, and transcriptomics. This review will first describe the biomarkers used in current practice and their limitations, and then summarize the current status of novel biomarkers for DKD with respect to assay-based protein biomarkers, proteomics, metabolomics, and transcriptomics.
The Evaluation of Cerebellum Gross Morphometric Measurements in Subjects Having Migraine, Ataxia, Dementia and Vertigo

GÖKER, . The evaluation of cerebellum gross morphometric measurements in subjects having migraine, ataxia, dementia, vertigo. Int. J. Morphol. , 40(4) :1067-1074, 2022. SUMMARY: This paper was aimed to determine the morphometric measurements of cerebellum using MRI in subjects having migraine, ataxia, dementia and vertigo. Three hundred twenty six (326 subjects; 80 migraine subjects; 85 vertigo subjects; 83 dementia subjects; 78 ataxia subjects) subjects ranging from 20 up to 85 years were included in this study. Cerebellum morphometric measurements were taken from subjects having brain MRI in the Radiology Department. The means and standard deviations of the measurements were: Sagittal section cerebellum superior inferior length, 56.21 – 5.16 mm; sagittal section cerebellum anteroposterior length, 86.36 – 5.36 mm; axial section cerebellum antereoposterior length, 66.53 – 5.41 mm; axial section bi-cerebellar length, 100.48 – 5.14 mm; coronal section cerebellum supero-inferior length,53.60 – 3.84 mm; coronal section bi-cerebellar length, 99.77 – 6.24 mm in subjects with migraine, whereas the corresponding values were 62.33 – 8.66 mm; 93.31 – 9.89 mm; 60.26 – 7.98 mm; 99.89 – 6.41 mm; 54.35 – 4.64 mm; 85.58 – 14.74 mm in subjects with vertigo, respectively. The same values were found as 58.82 – 8.34 mm; 86.74 – 13.22 mm; 58.93 – 8.89 mm; 97.93 – 6.07 mm; 50.66 – 4.92 mm; 84.96 – 14.93 mm in patients having dementia, respectively, while the same measurements were as 60.83 – 8.59 mm; 92.18 – 9.12 mm; 57.76 – 7.85 mm; 97.71 – 5.82 mm; 52.48 – 4.85 mm; 81.49 – 14.38 mm in ataxia patients, respectively. Also, ages were divided into seven groups as decades. There were found significant difference in all parameters according to sex and ages (p<0.05). The cerebellum morphometry provides important and useful knowledge in terms of comparison of abnormalities clinicians and data will be valuable for the determination of pathologies for clinical disciplines.
Characterization and application of hard x-ray betatron radiation generated by relativistic electrons from a laser-wakefield accelerator

The necessity for compact table-top x-ray sources with higher brightness, shorter wavelength and shorter pulse duration has led to the development of complementary sources based on laser-plasma accelerators, in contrast to conventional accelerators. Relativistic interaction of short-pulse lasers with underdense plasmas results in acceleration of electrons and in consequence in the emission of spatially coherent radiation, which is known in the literature as betatron radiation. In this article, we report on our recent results in the rapidly developing field of secondary x-ray radiation generated by high-energy electron pulses. The betatron radiation is characterized with a novel setup allowing to measure the energy, the spatial energy distribution in the far-field of the beam and the source size in a single laser shot. Furthermore, the polarization state is measured for each laser shot. In this way, the emitted betatron x-rays can be used as a non-invasive diagnostic tool to retrieve very subtle information of the electron dynamics within the plasma wave. Parallel to the experimental work, 3D particle-in-cell simulations were performed, proved to be in good agreement with the experimental results.
Screening in Hot Non-Abelian Plasma

This thesis is devoted to the study of the screening masses in hot non-Abelian theories. Section 1 contain a brief introduction to the topic. In section 2 a detailed overview of the screening phenomena and their applications is given. In section 3 the screening masses are defined through the coupled gap equations. Section 4 deals with the determination of the screening masses of hot SU(2) gauge theory in the framework of the 3d lattice adjoint Higgs model considered as an effective theory. Finally in section 5 the screening masses of hot SU(2) Higgs model are examined.
Using a discussion about scientific controversy to teach central concepts in experimental design

Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps rubella vaccine and autism controversy in the UK to illustrate a number of threshold concepts underlying good study design and interpretation of scientific evidence. These include the necessity of sufficient sample size, representative and random sampling, appropriate controls and inferring causation.
Análise de desempenho e produtividade de APIs baseadas em diretivas com suporte à programação paralela usando GPUs

OpenMP e OpenACC são modelos de programação desenvolvidos com o objetivo de abstrair a complexidade da programação paralela, proporcionando portabilidade entre diferentes arquiteturas, incluindo sistemas heterogêneos. Este trabalho busca fazer uma análise comparativa entre estes dois padrões, dos pontos de vista de produtividade de desenvolvimento e de desempenho computacional obtido. As avaliações foram conduzidas a partir da programação aderente aos padrões citados, aplicada a três algoritmos conhecidos, com execução em arquitetura que faz uso de GPUs. Os resultados, limitados à análise dos casos de estudo, mostram uma clara vantagem em desempenho e produtividade para o uso de OpenACC.
QUOTIENTS OF UNITAL A∞-CATEGORIES

Assuming that B is a full A∞-subcategory of a unital A∞-category C we construct the quotient unital A∞-category D =‘C/B’. It represents the A u-2-functor A 7→ A u (C, A)mod B, which associates with a given unital A∞-category A the A∞-category of unital A∞-functors C → A, whose restriction to B is contractible. Namely, there is a unital A∞-functor e : C → D such that the composition B → C e −→ D is contractible, and for an arbitrary unital A∞-category A the restriction A∞-functor (e ⊠ 1)M : A u (D, A) → A u (C, A)mod B is an equivalence. Let C k be the differential graded category of differential graded k-modules. We prove that the Yoneda A∞-functor Y : A → A u (A op , C k ) is a full embedding for an arbitrary unital A∞-category A. In particular, such A is A∞-equivalent to a differential graded category with the same set of objects. Let A be an Abelian category. The question: what is the quotient {category of complexes in A}/{category of acyclic complexes}? admits several answers. The first answer – the derived category of A – was given by Grothendieck and Verdier [Ver77]. The second answer – a differential graded category D – is given by Drinfeld [Dri04]. His article is based on the work of Bondal and Kapranov [BK90] and of Keller [Kel99]. The derived category D(A) can be obtained as H 0 (D pre-tr ).
Perturbative evaluation of scalar two-point function in the cosmic microwave background power spectrum

Recent work in the literature has found a suppression or, instead, an enhancement of the Cosmic Microwave Background power spectrum in quantum gravity, although the effect is too small to be observed, in both cases. The present paper studies in detail the equations recently proposed for a Born-Oppenheimer-type analysis of the problem. By using a perturbative approach to the analysis of the nonlinear ordinary differential equation obeyed by the two-point function for scalar fluctuations, we find various explicit forms of such a two-point function, with the associated power spectrum. In particular, a new family of power spectra is obtained and studied. The theoretical prediction of power enhancement at large scales is hence confirmed.
A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective

Molecular and sequencing technologies have been successfully used in decoding biological mechanisms of various diseases. As revealed by many novel discoveries, the role of non-coding RNAs (ncRNAs) in understanding disease mechanisms is becoming increasingly important. Since ncRNAs primarily act as regulators of transcription, associating ncRNAs with diseases involves multiple inference steps. Leveraging the fast-accumulating high-throughput screening results, a number of computational models predicting ncRNA-disease associations have been developed. These tools suggest novel disease-related biomarkers or therapeutic targetable ncRNAs, contributing to the realization of precision medicine. In this survey, we first introduce the biological roles of different ncRNAs and summarize the databases containing ncRNA-disease associations. Then, we suggest a new trend in recent computational prediction of ncRNA-disease association, which is the mode of action (MoA) network perspective. This perspective includes integrating ncRNAs with mRNA, pathway and phenotype information. In the next section, we describe computational methodologies widely used in this research domain. Existing computational studies are then summarized in terms of their coverage of the MoA network. Lastly, we discuss the potential applications and future roles of the MoA network in terms of integrating biological mechanisms for ncRNA-disease associations.
A PDE Approach to Value the Discrete Two-Asset Barrier Option

Discrete barriers introduce discontinuities in the solution of the option pricing partial differential equation (PDE) at discrete barriers' observation dates. An accurate solution to the pricing PDE requires a redefinition of the initial conditions at respective barrier observation dates. Since only the initial conditions are recursively imposed on the PDE, the pricing of the discrete two-asset barrier option can be defined as a sequence of the initial value problem. Thus, the recursive integral method is a highly efficient algorithm that calculates an accurate solution for the discrete two-asset barrier option. Key words: discrete two-asset barrier option, initial value problem, recursive integral method
POLARIMETRY IN THE HARD X-RAY DOMAIN WITH INTEGRAL SPI

We present recent improvements in polarization analysis with the INTEGRAL SPI data. The SPI detector plane consists of 19 independent Ge crystals and can operate as a polarimeter. The anisotropy characteristics of Compton diffusions can provide information on the polarization parameters of the incident flux. By including the physics of the polarized Compton process in the instrument simulation, we are able to determine the instrument response for a linearly polarized emission at any position angle. We compare the observed data with the simulation sets by a minimum χ2 technique to determine the polarization parameters of the source (angle and fraction). We have tested our analysis procedure with Crab Nebula observations and find a position angle similar to those previously reported in the literature, with a comfortable significance. Since the instrument response depends on the incident angle, each exposure in the SPI data requires its own set of simulations, calculated for 18 polarization angles (from 0° to 170° in steps of 10°) and unpolarized emission. The analysis of a large number of observations for a given source, required to obtain statistically significant results, represents a large amount of computing time, but it is the only way to access this complementary information in the hard X-ray regime. Indeed, major scientific advances are expected from such studies since the observational results will help to discriminate between the different models proposed for the high energy emission of compact objects like X-ray binaries and active galactic nuclei or gamma-ray bursts.
Cosmological perturbations in extended electromagnetism. General gauge invariant approach

A certain vector-tensor (VT) theory is revisited. It was proposed and analyzed as a theory of electromagnetism without the standard gauge invariance. Our attention is first focused on a detailed variational formulation of the theory, which leads to both a modified Lorentz force and the true energy momentum tensor of the vector field. The theory is then applied to cosmology. A complete gauge invariant treatment of the scalar perturbations is presented. For appropriate gauge invariant variables describing the scalar modes of the vector field (A-modes), it is proved that the evolution equations of these modes do not involve the scalar modes appearing in General Relativity (GR-modes), which are associated to the metric and the energy momentum tensor of the cosmological fluids. However, the A-modes modify the standard gauge invariant equations describing the GR-modes. By using the new formalism, the evolution equations of the A-perturbations are derived and separately solved and, then, the correction terms --due to the A-perturbations-- appearing in the evolution equations of the GR-modes are estimated. The evolution of these correction terms is studied for an appropriate scale. The relevance of these terms depends on both the spectra and the values of the normalization constants involved in extended electromagnetism. Further applications of the new formalism will be presented elsewhere.
Semi-Supervised Classification of Dual-Frequency PolSAR Image Using Joint Feature Learning and Cross Label-Information Network

Dual-frequency polarimetric synthetic aperture radar (PolSAR) data can provide more information than single-frequency data, which can effectively improve classification accuracy. However, how to obtain sufficient and nonredundant feature representation from dual-frequency PolSAR data remains to be resolved. Besides, deep learning has shown good performance in PolSAR image classification, but it often requires a large number of labeled samples to participate in the training process, which is time-consuming and labor-intensive. In this article, we propose a novel dual-frequency PolSAR image semi-supervised classification method that combines a dual-frequency joint feature learning (DFJFL) module with a cross label-information network (CLIN). First, the DFJFL module is developed based on the consistency and complementarity of dual-frequency data. It eliminates information redundancy by feature constraint loss function, and obtains compact dual-frequency joint feature representation. Subsequently, in order to avoid the influence of speckle noise, the proposed CLIN not only applies consistency regularization under network perturbation, but also uses the scattering mechanism of PolSAR data to find similar sample pairs to complete the consistency regularization under input perturbation, thereby achieving semi-supervised classification for PolSAR data. Experiments on four real dual-frequency PolSAR datasets verify that the proposed method can effectively extract dual-frequency PolSAR information, and make full use of unlabeled samples to improve classification accuracy. At the same time, compared with several related image classification algorithms, the proposed method could achieve the best performance.
IMPORTANCE OF INSTITUTIONAL CAPACITY FOR ATTRACTING FDI IN THE WESTERN BALKAN COUNTRIES

Foreign direct investments are an integral part of open and effective international economic system, and they are the main catalyst for development. However, the benefits of a foreign direct investment are not the same in all local communities, sectors and countries. International investments and national policy are aimed at foreign direct investment and reap benefits of investment development. The challenges are primarily related to the host countries, and the establishment of an efficient and transparent policy to attract investment, and that must be paid to building human and institutional capacity for their implementation. Compared to the existing literature, which focuses mainly on the effects of political risk or corruption on FDI, our contribution is reflected in testing a wider range of institutional variables and their impact on undertaking investment projects by foreign investors. The analysis included 5 countries of the Western Balkans in the period of 22 years starting from 1998 until 2019. In the analysis of empirical data, we used the fixed effect model (FEM) for evaluating FDI. Also, the quality of the research is promoted using balanced panel data.
Performance Analysis of the Milk Pasteurization Process Using a Flat Plate Solar Collector

A large share of Ethiopia’s milk production comes from its rural areas. However, this milk does not undergo further processing into dairy products on a large scale due to lack of conventional energy sources such as electricity and gas. Hence, the country is not utilizing its milk resources to the maximum possible. In this study, the possible use of solar energy for the milk pasteurization process is investigated by using a flat plate solar collector (FPSC) with and without reflectors integrated. Reflectors added to the FPSC have augmented the incident solar radiation on the collector from 0.27–0.91 kW/m2 to 0.36–1.18 kW/m2. The thermal efficiency obtained for the FPSC with reflectors integrated is 51.8% whereas that of the collector without reflectors integrated is 46.2%. Likewise, the exergy efficiency is found to be 5.43% for the collector integrated with reflectors and 2.53% for the collector without reflectors. Also, an increase in the daily processed milk production of 18% is observed in September and 16% in November by using the solar collector with reflectors integrated. The quality of pasteurized milk is checked by using the methylene blue reduction test (MBRT) method, and it indicates a better quality of pasteurized milk when compared with raw milk. Therefore, this study shows that the use of solar energy for milk pasteurization has great potential to increase the shelf life of milk, and it can be used as an instrument to improve the quality of life of people living in rural areas.
THE SOURCE DENSITY AND OBSERVABILITY OF PAIR-INSTABILITY SUPERNOVAE FROM THE FIRST STARS

Theoretical models predict that some of the first stars ended their lives as extremely energetic pair-instability supernovae (PISNe). With energies approaching 1053 erg, these supernovae are expected to be within the detection limits of the upcoming James Webb Space Telescope (JWST), allowing observational constraints to be placed on the properties of the first stars. We estimate the source density of PISNe using a semi-analytic halo mass function based approach, accounting for the effects of feedback from star formation on the PISN rate using cosmological simulations. We estimate an upper limit of ∼0.2 PISNe per JWST field of view at any given time. Feedback can reduce this rate significantly, e.g., lowering it to as little as one PISN per 4000 JWST fields of view for the most pessimistic explosion models. We also find that the main obstacle to observing PISNe from the first stars is their scarcity, not their faintness; exposures longer than a few times 104 s will do little to increase the number of PISNe found. Given this, we suggest a mosaic style search strategy for detecting PISNe from the first stars. Even rather high-redshift PISNe are unlikely to be missed by moderate exposures, and a large number of pointings will be required to ensure a detection.