Orthodontic treatment-related risks and complications: part II periodontal complications

Introduction: Orthodontic treatment, in addition to patient benefits, includes certain risks and complications that should not be ignored. The side-effects of orthodontic therapy all therapists want to avoid or reduce to a minimum.The occurrence of these complications depends on the orthodontic technique, medical knowledge in this field, patient\u27s general and oral health, and oral hygiene habits. Part of the risk and complications depend on the patient\u27s ability to understand and cooperate during the therapy. For this reason, it is a medico-legal obligation to inform our patients about side effects of any medical intervention what will be undertaken. In the previous issue, an overview of local complications of orthodontic treatment - dental complications was presented. The aim: The aim of this part is to present a detailed overview of the most common complications with local effect- periodontal complications in the context of the contemporary attitude of the risks and complications associated with orthodontic treatment. Material and methods: Classification was presented by Graber, 2004th, in its publication, "Risk Management in Orthodontics: AnExpert\u27s Guide to Malpractice," used as a starting point for the development of this review. A complex search was performed (PubMed, Google Scholar, etc.), with the restriction upon of publication date (beginning with 2004) to find relevant current studies. Search keywords were combinations of words: complication, orthodontic treatment, risks, side effects. Concluding remarks: Periodontal complications are the most common side effects linked with orthodontic treatment according to contemporary literature. Serious analysis of potential risk for periodontal complications is mandatory for orthodontic patients before the treatment starts. It is the only correct way to minimize complications during and after orthodontic treatment

Orthodontic treatment-related risks and complications: part I dental complications

Introduction: Orthodontic treatment is a complex medical intervention carried out over an extended period. During this time, risks may turn into complications. It is necessary to identify the risks that are associated with the orthodontic intervention to be applied, as there are numerous complications possibly linked to that treatment. The occurrence of these complications depends on the orthodontic technique, medical knowledge in this field, patient’s general and oral health, and oral hygiene habits. These must be considered even from the start because it might influence the treatment objectives, phases, and goals. Aim: of this study is to present a contemporary attitude of the main risks and complications linked to orthodontic interventions in clinical practice. Materials and methods: Classification presented by Graber et al. in publication, “Risk management in orthodontics: expert’s guide to malpractice,” is used as a starting point for the development of this review. A complex search was performed (Pubmed, Google scholar, etc.), with the restriction upon of publication date (beginning with 2004) to find relevant current studies. Search keywords were combinations of words: complication, orthodontic treatment, risks, side effects. Concluding remarks: According to contemporary literature, there are a lot of conditions to which orthodontic treatment can be linked. There is a medico-legal obligation to inform our patients about side effects of any medical intervention what will be undertaken

Evaluating temperature and precipitation extremes under 1.5°C and 2.0°C warming above pre-industrial levels: Botswana case study

The United Nations Framework Convention on Climate Change (UNFCCC) noted the need and therefore requested further quantitative research to better inform policy on the potential impacts of further warming to 1.5 and 2.0 °C above preindustrial levels. Climate extremes are expected to become more severe as the global climate continues to warm due to anthropogenic greenhouse gas emissions. The extent to which extremes and their impacts are to change due to additional 0.5 °C warming increments at regional level as the global climate systems warms from current levels to 1.5 and then 2.0 °C above preindustrial levels need to be understood to allow for better preparedness and informed policy formulation. Having realized the lack of research on this front in Botswana, this study investigates the differentiated impacts of climate change on climate extremes under the current, 1.5 and 2.0 °C warmer climates. The dissertation analysed the projected changes in extremes using Expert Team on Climate Change Detection and Indices (ETCCDI), derived from fifth version of Coupled Model Intercomparison Project (CMIP5) projections over Botswana, a country highly vulnerable to the impacts of climate change. Results indicate that (i) projected changes in temperature extremes are significantly different at the three levels of global warming, with hot day and night extremes expected to realise the greatest increases; (ii) drought related indices are also significantly different, and suggest progressively increasing drought risk with shortened rainfall seasons especially in northern Botswana; and (iii) heavy rainfall indices are likely to increase, but are not statistically different at the different global warming levels. The implications of these changes for key socio-economic sectors are explored, and reveal progressively severe impacts, and consequent adaptation challenges for Botswana as the global climate warms from its present temperature to 1.5 and then 2.0 °C

PREDICTORS OF POST-SECONDARY EMPLOYMENT AND EDUCATION AMONG KENTUCKY TRANSITION-AGED YOUTH WITH TRAUMATIC BRAIN INJURY

The State of Kentucky has a high and increasing number of reported cases of traumatic brain injury (TBI), mostly attributed to motor vehicle crashes, falls, and being struck by or against an object. Young adults are among those most at-risk for experiencing a TBI through motor vehicle crashes. Using existing data from the Kentucky Post-School Outcomes Center (KyPSO), 90 youth with TBI were identified within a period of 6-years of the longitudinal study (2012-2017). The majority were males and White. Descriptive statistics, chi square, and logistic regression were used to examine the post-secondary outcomes for youth with TBI, using four demographic variables: gender, ethnicity, residence, and rural or urban status. None of these were associated with post-secondary outcomes for the sample. The results indicated that more than 50% of the youth with TBI had positive outcomes, yet they rarely used the services provided for them in the schools or at the workplace. This study suggests that, although the demographic characteristics did not predict post-secondary outcomes, other variables within education and employment yielded interesting results that could benefit rehabilitation counselors

Health Education to Prevent Diarrhea in Preschoolers

Preschoolers are the second largest group suffering from diarrhea. Numerous studies have identified poor community hygiene and health practices contributing as causes of diarrhea, making it necessary to teach children healthy behavior for prevention. Healthy behavior can reduce the risk of diarrhea by 36–48%. Unfortunately, health education is commonly given to parents, but it is limited for children. Preschool is a period of transition from parental control to self-control. This period is also the best time to build concepts and ideas with constant reason. Applying an important concept for healthy behavior in this period will help to develop a child’s mindset in the future to prevent diarrhea. Health education to prevent diarrhea is pivotal to identify health behavior of preschoolers. When preschoolers’ health behavior has been identified, then it can be used to design an effective education model in preventing diarrhea

PERBANDINGAN MATRIKS PEMBOBOT SPASIAL OPTIMUM DALAM SPATIAL ERROR MODEL (SEM)

Matriks pembobot spasial merupakan komponen penting dalam kebanyakan model ketika representasi struktur spasial dibutuhkan. Karena hasil analisis sensitif terhadap spesifikasi matriks pembobot (W). Maka matriks bobot spasial yang berbeda mungkin diperlukan untuk berbagai jenis studi. Pada penelitian ini, peneliti melihat matriks pembobot optimum pada model SEM dengan menggunakan beberapa tipe matriks pembobot, di antaranya W Queen tidak terbakukan, W Queen terbakukan, W Rook, dan W Bishop. Dengan cara mngevaluasi nilai Akaike Information Criterion (AIC) terbaik dari dugaan model-model yang dihasilkan dari data Indeks Pembangunan Manusia (IPM) yang selanjutnya diperoleh pendekatan W terbaik dari hasil penelitian. Dari hasil penelitian ini dapat disimpulkan bahwa matriks pembobot tipe W Queen terbakukan merupakan model yang lebih baik dalam menjelaskan peubah respon karena memiliki nilai AIC yang terbaik bila dibandingkan dengan Matriks pembobot lainnya. Kata kunci : IPM, Analisis Regresi Spasial, SEM

Edgeworth expansion and bootstrap approximation for M-estimators of linear regression parameters with increasing dimensions

In this study, we consider two different inference problems in linear regression models. The first problem deals with the model y[subscript] j = x[subscript]spj\u27[beta] + [epsilon][subscript] j; j = 1,2, ...,n, where y[subscript]1,y[subscript]2, ...,y[subscript] n are observations; [epsilon][subscript]1,[epsilon][subscript]2, ...,[epsilon][subscript] n are independent and identically distributed random variables with a common distribution function; x[subscript]1,x[subscript]2, ...,x[subscript] n are known, nonrandom p-vectors; and [beta] is px1 vector of parameters. Edgeworth expansions for the standardized as well as studentized linear combinations of least squares estimators are obtained without assuming normal errors. The number of parameters p is allowed to increase with n and essentially under the condition p = O(n[superscript](1[over]2-[delta])) as n→[infinity] for any [delta] \u3e 0. These results extend the results of Qumsiyeh (1986). It is also shown that the bootstrap method is second order correct for the studentized statistics improving the results of Bickel and Freedman (1983);The second model is a p-population model given by Y[subscript]i = X[subscript] iB[subscript] i + [epsilon][subscript]i; i = 1,2, ...,p, where Y[subscript] i is the n[subscript] ix1 vector of observations from the i[superscript]th population; [epsilon][subscript] i is a n[subscript] ix1 random vector; [beta][subscript] i is the kx1 vector of parameters; and X[subscript] i is n[subscript] i xk known nonrandom matrix. Here k is a fixed positive integer and n[subscript] i≥ 1 denotes the i[superscript]th sample size for i = 1,2, ...,p. This is an extension of Ringland (1980) to a general regression model. Edgeworth expansions and bootstrap approximations of the M-estimator corresponding to some score function [psi] of the linear regression parameters are obtained under some regularity conditions on [psi] and on the error distribution function. This extends the results of Lahiri (1990) from fixed to increasing dimensionality. Results of this part remain valid under the condition p[superscript]3[over] N→ 0 as N→[infinity], where N = [sigma][subscript]spi=1p n[subscript] i is the number of observations

Analisis Penempatan Transformator Distribusi Berdasarkan Jatuh Tegangan Di PT PLN(Persero) ULP Malino

Dalam penyaluran energi listrik di mana lokasi pembangkit tenaga listrik berada jauh pada pusat beban memungkinkan terjadinya kerugian yang cukup besar dalam penyaluran energi listrik. Berdasarkan SPLN No. 72 tahun 1987, jatuh tegangan yang diizinkan untuk saluran udara tegangan menengah (SUTM) sebesar 5%. Penelitian ini bertujuan untuk mengetahui besarnya jatuh tegangan yang terjadi pada penyulang Lanna, PT. PLN (Persero) ULP Malino dan melakukan perbaikan jatuh tegangan tersebut. Penyulang Lanna mempunyai 61 buah gardu distribusi dengan kapasitas yang berbeda-beda. Jarak terjauh gardu distribusi dari pusat pembangkit sepanjang 52,995 Km. Metode penelitan dilakukan dengan persamaan atau rumus dan disimulasikan menggunakan Software Digsilent. Hasil penelitian ini  menunjukkan bahwa faktor-faktor yang mempengaruhi besarnya jatuh tegangan pada jaringan distribusi adalah arus beban puncak, panjang penghantar, luas penampang penghantar, dan faktor daya. Berdasarkan hasil perhitungan didapatkan bahwa gardu distribusi dengan kode gardu GT.LLN053 mengalami jatuh tegangan sebesar sebesar 1030,16 Volt atau sebesar 5,15%. Setelah dilakukan perbaikan berupa reposisi gardu distribusi, jatuh tegangan yang terjadi sebesar 956,41 Volt atau sebesar 4,78%