Heart diseases diagnosis using heart sounds

Heart sound is one of the oldest means for assessing the function of heart valves. It helps, together with echocardiograms and electrocardiographs, to give a clear and proper diagnosis of several diseases. Artificial neural networks are used to classify several valve-related heart disorders. A library of heart sound files, recorded via the traditional stethoscope, are used to extract relevant features using several signal processing tools, e.g., discrete wavelet transform (DWT), fast Fourier transform (FFT) and linear predictive coding (LPC). The achieved recognition rates were around 95.7%

Mapping Connections between Neighborhoods in Response to Community-Based Social Needs

Geographic proximity might not be the only factor influencing the connections between neighborhoods within the same city. Most likely, the community's needs and behaviors play a role in facilitating or hindering any connections between these urban areas. Accordingly, relationships between communities may differ or be similar based on their respective characteristics. This paper aims to demonstrate that communities are close based on the needs they share, regardless of their ethnicity or geographic location. In this study, a time series analysis of neighborhoods' needs is explored to gain a deeper understanding of the communities' network. The study takes into account the co-occurrence of complaints/reports from residents regarding the same issue. The dataset was retrieved from the Boston Area Research Initiative (BARI) and the 311 system that describe the features of neighborhoods regarding non-emergency issues. Subsequently, the connection between neighborhoods in the City of Boston was analyzed using a mixture of PCA, K-means, association rule mining, and a network creation tool. Moreover, clustering coefficients and degrees of centrality were used as significant factors in identifying the members of groups and marking crucial nodes in the network. A series of graphs were generated to show how the neighborhoods are linked based on their socioeconomic concerns. The results prove that even geographically disconnected neighborhoods within Boston have similar social needs, despite their distance from one another. Furthermore, it revealed that some neighborhoods can act as linking bridges for other neighborhoods, while others may be isolated within the network graph. This study has increased awareness of urban aspects. The authorities may consider other dimensions than the traditional ones regarding neighborhood development and addressing problems. Finally, it helps to identify common characteristics between neighborhoods, which facilitates the policy making process

Adomian’s decomposition method to modeling power functionally graded thermoelastic materials in heat transfer and thermal stress analysis

This work deals with an iteration method for numerical solving the problem of one-dimensional coupled thermoelasticity under given boundary conditions. This iteration based on the Adomian’s decomposition method. All the material properties have been considered variable on position with a power law. The numerical results have been calculated for different cases of the gradient parameter and the gradient index. The numerical results have been shown in figures. The gradient parameter and the gradient index have significant effects on the temperature increment, the strain, the stress, and the displacement

Heart diseases diagnosis using HMM

The bare ear and the stethoscope were until recently of great help in classifying most heart diseases especially those related to valve problems. The newly developed electronic stethoscope and phonocardiography represent useful tools for recording heart sound signals. In this paper a diagnostic technique for heart diseases using heart sounds is suggested. Wavelet decomposition and mel cepstrum are used for feature extraction. Classification of the different heart diseases is then done using hidden Markov models (HMM). Three different techniques have been used and compared. The obtained recognition rates (RR) were 97.3%, 98.2%, and 99.1%

Effect of Blast Loading on Seismically Detailed RC Columns and Buildings

Explosions caused by standoff charges near buildings have drastic effects on the internal and external structural elements which can cause loss of life and fatal injuries in case of failure or collapse of the structural element. Providing structural elements with blast resistance is therefore gaining increasing importance. This paper presents numerical investigation of RC columns with different reinforcement detailing subjected to near-field explosions. Detailed finite element models are made using LS-DYNA software package for several columns having seismic and conventional reinforcement detailing which were previously tested under blast loads. The numerical results show agreement with the published experimental results regarding displacements and damage pattern. Seismic detailing of columns enhances the failure shape of the column and decrease the displacement values compared to columns with conventional reinforcement detailing. Further, the effect of several modeling parameters are studied such as mesh sensitivity analysis, inclusion of air medium and erosion values on the displacements and damage pattern. The results show that decreasing the mesh size, increasing erosion value and inclusion of air region provide results that are very close to experimental results. Additionally, application is made on a slab-column multistory building provided with protective walls having different connection details subjected to blast loads. The results of this study are presented and discussed. Use of a top and bottom floor slab connection of protective RC walls are better than using the full connection at the four sides to the adjacent columns and slabs. This leads to minimizing the distortion and failure of column, and therefore it increases the chance of saving the building from collapse and saving human lives. Doi: 10.28991/cej-2021-03091733 Full Text: PD

Addressing patient treatment preferences at trial recruitment.

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MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities

Urbanism is no longer planned on paper thanks to powerful models and 3D simulation platforms. However, current work is not open to the public and lacks an optimisation agent that could help in decision making. This paper describes the creation of an open-source simulation based on an existing Dutch liveability score with a built-in AI module. Features are selected using feature engineering and Random Forests. Then, a modified scoring function is built based on the former liveability classes. The score is predicted using Random Forest for regression and achieved a recall of 0.83 with 10-fold cross-validation. Afterwards, Exploratory Factor Analysis is applied to select the actions present in the model. The resulting indicators are divided into 5 groups, and 12 actions are generated. The performance of four optimisation algorithms is compared, namely NSGA-II, PAES, SPEA2 and eps-MOEA, on three established criteria of quality: cardinality, the spread of the solutions, spacing, and the resulting score and number of turns. Although all four algorithms show different strengths, eps-MOEA is selected to be the most suitable for this problem. Ultimately, the simulation incorporates the model and the selected AI module in a GUI written in the Kivy framework for Python. Tests performed on users show positive responses and encourage further initiatives towards joining technology and public applications.Comment: 16 page

Garay’s Condition of Deformed Cylindrical and Translation Surfaces in E3

The motivation of the present work is to develop the finiteness property in our work [1, 2, 3, 4] by using Garay’s condition [5]. The mean curvature flow and the finiteness property of the cylindrical surfaces in E3 are investigated. Additionally, the linear deformation of such surfaces is studied. Finally, the translation surfaces are discussed

Renoprotective effect of red grape (Vitis vinifera L.) juice and dark raisins against hypercholesterolaemia-induced tubular renal affection in albino rats

Background: Red grape juice (RGJ) and dark raisins (DR) are rich in polyphenols and antioxidants. This study aimed to assess the efficacy of RGJ and DR in protec- ting the renal tubules against hypercholesteraemic-induced pathological changes.  Materials and methods: Forty albino rats divided into four groups (n = 10) were utilised in this study. They included the control, high cholesterol diet (HCD)-fed, HCD+RGJ-fed, and HCD+DR-fed groups. Body weight gain, food and water in- take, blood and insulin levels, lipid profile and kidney functions were assessed at the start of the experiment and after 12 weeks. The right kidney was dissected out and processed for both light and electron microscopic examination. Desmin and cytokeratin antibodies were utilised as histologic markers to assess the integrity of the proximal (PTs) and distal tubules (DTs) of the kidney.  Results: Administration of HCD resulted in hypercholesterolaemia in rats as evi- denced by the lipid profile. The PTs of hypercholesteraemic rats appeared dilated with hyaline casts and mitochondria in most of the tubular cells were affected. Immunohistochemical assessment revealed affection of both PTs and DTs. Both RGJ and DR, when administered along with the HCD for 12 weeks, improved the lipid profile, kidney functions as well as the histologic and cellular changes-induced by hypercholesterolaemia in the rats. The effect of raisins was superior to RGJ which might be due to its high contents of fibres and proteins.  Conclusions: This study highlighted the importance of supplementation of red grape and raisins in protection against the harmful effects induced by deposition of fat on the renal tubules’ structure and function.