Background: Calcaneus is a spongy cancellous bone with rich blood supply , its fracture heals more rapidly providing no occurrence of infection and soft tissue injury around ,no gross malposition of fragments. The associated pain leads to a major impairment in life quality. The aim of treatment for calcaneal fractures is the decrease of pain and rebuilding of walking ability for patients with normal foot shape and the ability to wear normal foot wear. To reduce complications, a minimally invasive technique for the treatment of displaced intra-articular fractures of the calcaneus was preferred to use. The purpose of this study was to determine whether the closed reduction and percutaneous K. wire fixation of displaced intra-art

To investigate the efficacy of polyether‐ether‐ketone (PEEK) wire as a fixed orthodontic retainer, by comparing its performance to other retainer wires and optimizing its adhesion to composite bonding materials.

Background: Calcaneus is a spongy cancellous bone with rich blood supply , its fracture heals more rapidly providing no occurrence of infection and soft tissue injury around ,no gross malposition of fragments. The associated pain leads to a major impairment in life quality. The aim of treatment for calcaneal fractures is the decrease of pain and rebuilding of walking ability for patients with normal foot shape and the ability to wear normal foot wear. To reduce complications, a minimally invasive technique for the treatment of displaced intra-articular fractures of the calcaneus was preferred to use.

The purpose of this study was to determine whether the closed reduction and percutaneous K. wire fixation of displ

Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

This work represents development and implementation a programmable model for evaluating pumping technique and spectroscopic properties of solid state laser, as well as designing and constructing a suitable software program to simulate this techniques . A study of a new approach for Diode Pumped Solid State Laser systems (DPSSL), to build the optimum path technology and to manufacture a new solid state laser gain medium. From this model the threshold input power, output power optimum transmission, slop efficiency and available power were predicted. different systems configuration of diode pumped solid state laser for side pumping, end pump method using different shape type (rod,slab,disk) three main parameters are (energy transfer efficie

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

In Iraq, water shortages and drought, especially during the hot summer months, necessitates that municipal authorities adopt water reuse projects like reusing treated domestic wastewater for crop irrigation. This work gives the conceptual and basic design elements for the necessary steps of filtration, UV irradiation and chlorination to make such a wastewater fit for agricultural use. A typical rural community of 50,000 people is considered as an example case for which functionality and relative simplicity of the proposed designs are prime factors. The objectives are 1) to show what is required and 2) that the presented information may be utilized to embark on the following phases of detailed design and execution of such projects.

Sliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control