Comparative Study on the Early Stage of Skid Resistance Development between Polyurethane-Bound Porous Mixture and Asphalt Mixture

The article presents the results of a study to assess the functional reserve of the kidneys against the background of a comparative study of antiaggregant therapy dipyridamole and allthrombosepin in 50 patients with a relatively early stage of chronic kidney disease. Studies have shown that long-term administration of allthrombosepin to patients has resulted in better maintenance of kidney functional reserves. Therefore, our research has once again confirmed that diphtheridamol, which is widely used as an antiaggregant drug in chronic kidney disease, does not lag behind the domestic raw material allthrombosepin

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Comparative Study on Asphalt Mixture with Nano Materials and Polymer

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1112/1/012019 ◽

2021 ◽

Vol 1112 (1) ◽

pp. 012019

Author(s):

Akhila Bobbili ◽

Sai Krishna Kollipara ◽

V. Mallikarjuna ◽

Malathi Narra

Keyword(s):

Comparative Study ◽

Asphalt Mixture ◽

Nano Materials

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A Comparative Study of Alzheimer Detection Techniques

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2021.37882 ◽

2021 ◽

Vol 9 (8) ◽

pp. 2877-2883

Author(s):

Adwait Patil

Keyword(s):

Machine Learning ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Deep Learning ◽

Comparative Study ◽

Fuzzy System ◽

Early Stage ◽

Machine Learning Algorithms ◽

Support Vector ◽

Detection Techniques

Abstract: Alzheimer’s disease is one of the neurodegenerative disorders. It initially starts with innocuous symptoms but gradually becomes severe. This disease is so dangerous because there is no treatment, the disease is detected but typically at a later stage. So it is important to detect Alzheimer at an early stage to counter the disease and for a probable recovery for the patient. There are various approaches currently used to detect symptoms of Alzheimer’s disease (AD) at an early stage. The fuzzy system approach is not widely used as it heavily depends on expert knowledge but is quite efficient in detecting AD as it provides a mathematical foundation for interpreting the human cognitive processes. Another more accurate and widely accepted approach is the machine learning detection of AD stages which uses machine learning algorithms like Support Vector Machines (SVMs) , Decision Tree , Random Forests to detect the stage depending on the data provided. The final approach is the Deep Learning approach using multi-modal data that combines image , genetic data and patient data using deep models and then uses the concatenated data to detect the AD stage more efficiently; this method is obscure as it requires huge volumes of data. This paper elaborates on all the three approaches and provides a comparative study about them and which method is more efficient for AD detection. Keywords: Alzheimer’s Disease (AD), Fuzzy System , Machine Learning , Deep Learning , Multimodal data

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Comparative study of the detection of joint injury in early-stage rheumatoid arthritis by MRI of wrist and finger joints and physical examination

Arthritis Care & Research ◽

10.1002/acr.20395 ◽

2010 ◽

pp. n/a-n/a ◽

Cited By ~ 2

Author(s):

Mami Tamai ◽

Atsushi Kawakami ◽

Naoki Iwamoto ◽

Shin-ya Kawashiri ◽

Keita Fujikawa ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Physical Examination ◽

Comparative Study ◽

Early Stage ◽

Joint Injury ◽

Finger Joints

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Expansion Level of Steel Slag Aggregate Effects on Both Material Properties and Asphalt Mixture Performance

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119835513 ◽

2019 ◽

Vol 2673 (3) ◽

pp. 506-515 ◽

Cited By ~ 6

Author(s):

Jamilla Emi Sudo Lutif Teixeira ◽

Aecio Guilherme Schumacher ◽

Patrício Moreira Pires ◽

Verônica Teixeira Franco Castelo Branco ◽

Henrique Barbosa Martins

Keyword(s):

Material Properties ◽

Mechanical Performance ◽

Early Stage ◽

Asphalt Binder ◽

Steel Slag ◽

Asphalt Mixture ◽

Asphalt Mixtures ◽

Mix Design ◽

Expansion Level ◽

Different Levels

The influence of steel slag expansion level on the early stage performance of hot mix asphalt (HMA) is evaluated. Initially, samples of Linz-Donawitz type steel slag with different levels of expansion (6.71%, 3.16%, 1.33%) were submitted to physical, mechanical, and morphological characterization to assess the effects of expansion on individual material properties. Steel slag was then used as aggregate in HMA to verify the effects of its expansion characteristics on the volumetric and mechanical performance of the asphalt mixture. Four different asphalt mixtures were designed based on Marshall mix design, using asphalt cement (pen. grade 50/70), natural aggregate (granite), and steel slag (in three different levels of expansion). The mechanical characteristics of the asphalt mixture were evaluated based on results from Marshall stability, indirect tensile strength, and resilient modulus testing. A modified Pennsylvania testing method (PTM) was also performed on the studied asphalt mixtures to verify the potential of asphalt binder film to minimize the expansive reactions of steel slag. It was observed that the level of steel slag expansion changes some of the material’s individual properties, which can affect the volumetric parameters of the mix design. The use of steel slag as aggregate in HMA also improves the mechanical properties of non-aged asphalt mixtures. Moreover, the expansive characteristics of this material could be minimized when combined with other asphalt mixture components.

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