Effect of lumbar lordosis angle in adolescent baseball players on the development of lumbar spondylolysis v1

Background: Lumbar spondylolysis is a stress fracture of the lumbar vertebral arch that occurs frequently in adolescents. Lumbar spondylolysis has a high prevalence in athletes, especially baseball players. When lumbar spondylolysis occurs, restriction of sports activities is inevitable until the bony union is achieved. Therefore, prevention of the onset of lumbar spondylolysis is necessary, and it is necessary to elucidate the risk factors that influence the onset of the disease. An increase in lumbar lordosis angle may influence the development of lumbar spondylolysis because the lumbar lordosis angle increases the compressive stress in the vertebral arch. However, there are no reports on the effect of lumbar lordosis angle and the development of lumbar spondylolysis in adolescent baseball players. Therefore, the purpose of this study was to investigate the effect of lumbar lordosis angle on the development of lumbar spondylolysis in adolescent baseball players. METHODS: Eligible patients were those who visited the orthopedic clinic from January 1, 2018, to October 31, 2021. The selection criteria were male baseball players aged 11-18 years who visited the clinic, and the exclusion criteria were those whose superior endplate of L1 and superior endplate of S1 could not be identified in the MRI images. The existence of development of lumbar spondylolysis, lumbar lordosis angle, age, and pitching experience of the above patients will be assessed based on electronic medical records and imaging findings. Statistical analysis was performed using logistic regression analysis, with the objective variable being the existence of lumbar spondylolysis and the explanatory variables being the lumbar lordosis angle, age, and previous pitching experience.Discussion: This study examines the effect of the lumbar lordosis angle on the development of lumbar spondylolysis in adolescent baseball players. An increase in lumbar lordosis angle may influence the development of lumbar spondylolysis and may be a risk factor for the development of lumbar spondylolysis.

The Relationship between Income and Morbidity—Longitudinal Findings from the German Ageing Survey

It is often assumed that higher income contributes to physical health. Indeed, there is a huge amount of research showing a strong significant association between income and health. However, very few studies have used longitudinal data and an objective variable for health, such as morbidity. Therefore, this study aims to examine the association between the income and morbidity of individuals over time. Data from a total of four waves (year 2008 to year 2017) of the nationally representative German Ageing Survey was analyzed by linear fixed-effects regressions. The used equivalized income was based on the respondents’ monthly net household income. To obtain a comprehensive picture of the dependent variable morbidity, self-reported diseases, current symptoms, and physician-diagnosed diseases were examined. The analyses showed no significant association between percentage changes in income and morbidity in the total sample. Even after considering selected socioeconomic groups in further subgroup analyses, there was no significant within-person association found over time. In summary, the unexpected results of this study suggest that the previously assumed link between income and health in Germany may be called into question. Further research based on longitudinal studies is, therefore, required.

Multi-Objective Variable Neighborhood Strategy Adaptive Search for Tuning Optimal Parameters of SSM-ADC12 Aluminum Friction Stir Welding

This research presents a novel algorithm for finding the most promising parameters of friction stir welding to maximize the ultimate tensile strength (UTS) and maximum bending strength (MBS) of a butt joint made of the semi-solid material (SSM) ADC12 aluminum. The relevant welding parameters are rotational speed, welding speed, tool tilt, tool pin profile, and rotation. We used the multi-objective variable neighborhood strategy adaptive search (MOVaNSAS) to find the optimal parameters. We employed the D-optimal to find the regression model to predict for both objectives subjected to the given range of parameters. Afterward, we used MOVaNSAS to find the Pareto front of the objective functions, and TOPSIS to find the most promising set of parameters. The computational results show that the UTS and MBS of MOVaNSAS generate a 2.13% to 10.27% better solution than those of the genetic algorithm (GA), differential evolution algorithm (DE), and D-optimal solution. The optimal parameters obtained from MOVaNSAS were a rotation speed of 1469.44 rpm, a welding speed of 80.35 mm/min, a tool tilt of 1.01°, a cylindrical tool pin profile, and a clockwise rotational direction.

Corrosion Predictive Model in Hot-Dip Galvanized Steel Buried in Soil

Corrosion is one of the main concerns in the field of structural engineering due to its effect on steel buried in soil. Currently, there is no clearly established method that allows its calculation with precision and ensures the durability of this type of structures. Qualitative methods are commonly used rather than quantitative methods. The objective of this research is the development of a multivariate quantitative predictive model for estimating the loss of thickness that will occur in buried hot-dip galvanized steel as a function of time. The technique used in the modelling is the Adaptive Regression of Multivariate Splines (MARS). The main drawback of this kind of studies is the lack of data since it is not possible to have a priori the corrosive behaviour that the buried material will have as a function of time. To solve this issue, a solid and reliable database was built from the analysis and treatment of the existing literature and with the results obtained from a predictive model to estimate the thickness loss of ungalvanized steel. The input variables of the model are 5 characteristics of the soil, the useful life of the structure, and the loss of corroded ungalvanized steel in the soil. This last data is the output variable of another previous predictive model to estimate the loss of thickness of bare steel in a soil. The objective variable of the model is the loss of thickness that hot-dip galvanized steel will experience buried in the ground and expressed in g/m2. To evaluate the performance and applicability of the proposed model, the statistical metrics RMSE, R2, MAE, and RAE and the graphs of standardized residuals were used. The results indicated that the model offers a very high prediction performance. Specifically, the mean square error was 290.6 g/m2 (range of the objective variable is from 51.787 g/m2 to 5950.5 g/m2), R2 was 0.96, and from a relative error of 0.14, the success of the estimate was 100%. Therefore, the use of the proposed predictive model optimizes the relationship between the amount of hot-dip galvanized steel and the useful life of the buried metal structure.

Selection Method of Molding Condition for Self-Adhesive Products Using Only Bamboo Fibers Extracted With a Machining Center Based on Bayesian Optimization

Bamboo grows naturally in Japan as an underutilized forest resource, and its fibers have high specific strength and stiffness, so much so that they are called natural glass fibers. In this study, a method for manufacturing a self-adhesive compact material by pressurizing and heating 100% bamboo fiber after extraction using a machining center, without losing the composition of bamboo, is proposed. This molded body is made of a 100% natural material and has a low environmental impact even when landfilled, contributing to the growth of bamboo for use as a raw material. In this study, the formation conditions for maximizing the tensile properties when forming platelets were investigated. First, an analysis of the variance was conducted using the orthogonal array test design to identify the factors affecting the objective variable and determine the contribution of each factor. In addition, estimates of the objective variable for the molding conditions were obtained from the Gaussian process regression model in a Bayesian optimization. Furthermore, as a result of comparing the maximum values of the properties of the molding conditions between the analysis of variance and the Gaussian process regression model, the values of the tensile properties were improved in the Gaussian process regression model.

Analisis pengaruh promosi dan margin terhadap keputusan pengambilan kredit kepemilikan rumah (KPR) syariah

Bank Indonesia's Monetary and Fiscal Statistics data shows that financing provided by all types of banks in Indonesia increased by Rp. 504.494 billion in 2019 to Rp 513.528 billion in October 2020. Banking in Indonesia that has a focus in the Home Ownership Credit sector is Bank Syariah Indonesia with both Conventional and Sharia system. This study uses a descriptive quantitative approach due to the aspect of objective variable measurement with numbers in analyzing data using statistical procedures. The nature of this study is a correlation meaning that this study will look for the influence of promotion and also margin on sharia home ownership credit (HOM) decision making. Based on the research that has been done, it can be concluded that:(1) There is a significant influence between the promotion of sharia home ownership loan (HOM) decision at Bank Syariah Indonesia Soekarno-Hatta Malang Branch. This is evidenced by the existence of customers who take a mortgage after learning of the promotion from the bank. (2) Variable x2 margin has no effect on sharia mortgage decision making due to what happens in the field of respondents choosing to take HOM due to subsidies from the government. (3) There is a significant influence between promotion and margin on sharia home ownership credit decision making at Bank Syariah Indonesia Soekarno Hatta Branch. Abstrak Data Statistik Moneter dan Fiskal Bank Indonesia menunjukan pembiayaan yang diberikan oleh seluruh jenis Bank yang ada di Indonesia mengalami peningkatan yaitu sebesar Rp. 504,494 Miliar di Tahun 2019 meningkat menjadi Rp 513,528 Miliar pada Oktober Tahun 2020. Perbankan di Indonesia yang memiliki fokus di sektor Kredit Pemilikan Rumah adalah Bank Syariah Indonesia baik dengan sistem Konvensional maupun Syariah. Penelitian ini menggunakan pendekatan kuantitatif deskriptif dikarenakan aspek pengukuran variabel secara objektif dengan angka dalam menganalisis data menggunakan prosedur statistika. Sifat penelitian ini adalah korelasi artinya penelitian ini akan mencari ada tidaknya pengaruh antara promosi dan juga margin terhadap keputusan pengambilan kredit kepemilikan rumah (KPR) Syariah. Berdasarkan penelitian yang telah dilakukan, dapat disimpulkan bahwa: (1) Terdapat pengaruh yang signifikan antara promosi terhadap keputusan pengambilan kredit kepemilikan rumah (KPR) syariah di Bank Syariah Indonesia Cabang Soekarno–Hatta Malang. Hal ini dibuktikan dengan adanya nasabah yang mengambil KPR setelah mengetahui promosi dari bank tesebut. (2) Variabel x2 margin tidak berpengaruh terhadap pengambilan keputusan KPR Syariah disebabkan hal yang terjadi di lapangan responden memilih mengambil KPR dikarenakan subsidi dari pemerintah. (3) Terdapat pengaruh signifikan antara promosi dan margin terhadap pengambilan keputusan kredit kepemilikan rumah syariah di Bank Syariah Indonesia Cabang Soekarno Hatta.

Fuzzy Linear Programming Dalam Optimalisasi Pelayanan Air Bersih Perusahaan Daerah Air Minum (PDAM) Kab. Jeneponto Menggunakan Metode Sabiha

Abstrak. Fuzzy linear programing merupakan pengembangan model program linear dalam menentukan nilai optimal yang mengandung bilangan fuzzy. Metode yang dapat digunakan dalam menyelesaikan fuzzy linear programing yaitu metode Sabiha. Penggunaan metode Sabiha didasarkan pada bilangan linear fuzzy real yang berbentuk bilangan triplet. Pada penelitian ini digunakan model Fuzzy linear programing dalam menentukan nilai optimal pelayanan PDAM Kab. Jeneponto dengan metode sabiha. Menyusun setiap indikator fungsi tujuan (Z) dan fungsi kendala untuk dioptimalkan.. Hasil penyelesaian model diperoleh nilai optimal total pelanggan 9075,999999999990. Untuk setiap variabel tujuan dengan nilai optimal 8896, 999999999990 untuk jenis pelanggan rumah tangga, 96,0000000000112 untuk jenis pelanggan sosial khusus, dan 82,9999999999982 untuk jenis pelanggan sosial umum. Dengan total pendapatan optimal Rp. 4.753.125.000 dan total permintaan air 1.082.303 m3.Kata Kunci : Program Linear, Fuzzy Linear Programing, Linear Fuzzy Number. Metode Sabiha, Optimalisasi.Abstract. Linear fuzzy programing is advance model for linear programing to determin the optimal result that contains fuzzy numbers. Linear Fuzzy programing can be solved using Sabiha’s method. Which is based on real linear fuzzy numbers in triplet numbers form. This paper used linear fuzzy programming model and Sabiha’s method, to determin the optimal solution on PDAM Kab. Jeneponto’s operation plan. Each indicator constructed to optimized objective function and constraint function. Results of this research have optimal solution for each objective variable was obtained with an optimal value for total costumer are 9075,999999999990 from 8896,999999999990 the type of household customer, 96,0000000000112 the type of special social customer, and 82,9999999999982 the type of public social costumer. With an optimal total revenue Rp. 4,753,125,000 and total water demand 1,082,303 m3.Keywords: Linear Programing, Linear Fuzzy Programing, Linear Fuzzy Number, Sabiha’s Method, Optimalization.

A Multi-Objective Variable Neighborhood Search Algorithm for Precast Production Scheduling

In real life, precast production schedulers face the challenges of creating a reasonable schedule to satisfy multiple conflicting objectives. Practical constraints and objectives encountered in the precast production scheduling problem (PPSP) were addressed, with the goal to minimize makespan and total earliness and tardiness penalties. A multi-objective variable neighborhood search (MOVNS) algorithm was proposed and the performance was tested on 11 problem instances. Ten of these were generated using precast concrete production information taken from the literature. One real industrial problem from a precast concrete company was considered as a case study. Extensive experiments were conducted, and the spread and distance metrics were used to evaluate the quality of the non-dominated solutions set. Statistical analysis demonstrated that the result was statistically convincing. Computational results showed that the proposed MOVNS algorithm was significantly better when compared to the other nine algorithms. Therefore, the proposed MOVNS algorithm was a very competitive method for the considered PPSP.