A research on reasons of forest crımes: karadere forests admınıstratıon model

İnsanoğlunun varoluşu ile başlayan suç kavramı bugünde varlığını sürdürmektedir. Ormanlarda insan müdahaleleri sonucu oluşan zararların büyük bir bölümü kırsal kesimde yaşayan özelliklede orman köylüsü tarafından yapılmaktadır. Orman suçları olarak adlandırılan bu eylemler ülkemizde halen görülmekte ve bir sorun olarak karşımızda durmaktadır. Birçok nedene bağlı olarak ortaya çıkan orman suçlarının, ormanların varlığı ve sürdürülebilirliği üzerinde çok çeşitli etkileri mevcuttur. Bu çalışmada Kastamonu Orman Bölge Müdürlüğü’nde orman suçlarının yoğun olarak görüldüğü Karadere Orman işletme Müdürlüğü’ndeki orman suçlarının durumu ortaya konarak, nedenleri araştırılmaya çalışılmıştır. Bu amaçla işletme müdürlüğü sınırları içerisindeki 36 orman köyünde 236 orman köylüsü ile görüşülerek orman suçlarına etki eden faktörler belirlenmeye çalışılmıştır.The concept of crime which came into stage with the creation of the man still exists today. The damage which is done on the forestry areas by the human impact is to a great extent- done by the people who live in or near these areas. These crimes which we will call as the forestry crimes can be seen in our country as a serious problem to be solved. There are several reasons which make people commit these crimes, and the crimes have serious effects on the continuity and the existence of the forests. In this study, the reasons of the forestry crimes are examined by using the data gathered from a field study in Karadere Forests Administration a section in Kastamonu Regional Direct rote of Forests- where crimes are intensively take place. By meeting and interviewing 236 villagers who reside in 36 different villages, the factors which result in forestry crimes are tried to be determined

Coupled nonparametric shape priors for segmentation of multiple basal ganglia structures

This paper presents a new method for multiple structure segmentation, using a maximum a posteriori (MAP) estimation framework, based on prior shape densities involving nonparametric multivariate kernel density estimation of multiple shapes. Our method is motivated by the observation that neighboring or coupling structures in medical images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our technique allows simultaneous segmentation of multiple objects, where highly contrasted, easy-to-segment structures can help improve the segmentation of weakly contrasted objects. We demonstrate the effectiveness of our method on both synthetic images and real magnetic resonance images (MRI) for segmentation of basal ganglia structures

Modelling and simulation studies on adaptive controller for alt-azimuth telescopes despite unknown wind disturbance and mass

Numerous ground-based observatories are using small sized ground telescopes for scientific research purposes. The telescopes that are available on the market have three main problems. These issues can be listed as: positioning repeatability, tuning requirement according to different wind speeds for different seasons, and the mass changing via different scientific equipments added to the telescope. This study is aimed at resolving these issues for ground based small alt-azimuth telescopes. Establishing of a set and forget system is performed by designing an adaptive controller. Motor dynamics are taken into consideration for a realistic mathematical model. The Wind-Gust model that consists of a sum of sinusoidal disturbances with unknown phase, amplitude and frequency is used for the wind model. The purposed controller cancels the disturbance effects on the plant while operational positioning and also the makes the plant insensitive to mass changes. The Lyapunov approach is utilised when proving the asymptotic stability. The proposed controller’s success is illustrated with thorough numerical evaluation.The authors would like to thank the technical guidance and funding support of Isik University, Center for Optomechatronics Research and Application (OPAM),and Ataturk University Center for Astrophysical Application and Research (ATASAM). The author(s) received no financial support for the research, authorship, and/or publication of this article.Publisher's Versio

Larinks skuamöz hücreli karsinom kökenli optik disk ve koroid metastazlı bir olgu

A 67-year-old male patient was presented with loss of vision, which he noticed in his left eye one week ago. He had undergone total laryngectomy due to laryngeal squamous cell carcinoma 3 years ago. His fundus examination revealed an elevated yellow mass on the optic disc. Magnetic resonance imaging (MRI) and computed tomography (CT) were performed with suspicion of laryngeal cancer metastasis. The MRI showed metastatic lesions in the brain, optic disc, and the surrounding choroid. The CT demonstrated diffuse metastasis in both lungs. The patient received radiotherapy for the brain, optic disc, and choroidal metastases. Unfortunately, the patient died within 2.5 months after the diagnosis because of systemic complications that developed due to extraocular causes. Metastasis of laryngeal cancer to the optic disc and choroid is rare. Although the majority of optic disc tumors are primary, a systemic investigation should be performed in cases of a mass on the disc with the suspicion of distant organ metastasis, albeit rare.T Altmış yedi yaşında erkek hasta, 1 hafta önce sol gözünde fark ettiği görme kaybı şikâyeti ile başvurdu. Üç yıl önce laringeal skuamöz hücreli karsinom nedeniyle total larenjektomi geçirdiği öğrenildi. Fundus muayenesinde, optik diskte sarı bir kitle görüldü. Larinks kanseri metastazı şüphesi ile manyetik rezonans görüntüleme (MRG) ve bilgisayarlı tomografi (BT) yapıldı. MRG’de beyin, optik disk ve çevreleyen koroidde, metastatik lezyonlar tespit edildi. BT’de her iki akciğerde yaygın metastaz saptandı. Hasta beyin, optik disk ve koroid metastazları için radyoterapi aldı. Ekstraoküler nedenlere bağlı gelişen sistemik komplikasyonlar nedeniyle tanı konulduktan sonraki 2,5 ay içinde ne yazık ki hasta kaybedildi. Larinks kanserinin, optik disk ve koroide metastazı nadirdir. Optik disk tümörlerinin çoğunluğu primer olmakla birlikte, nadir de olsa uzak organ metastazı şüphesi ile diskte kitle olması durumunda sistemik inceleme yapılmalıdır

Volumetric segmentation of multiple basal ganglia structures

We present a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. Neighboring anatomical structures in the human brain exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities based on training data, we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework, and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We compare our technique with existing methods and demonstrate the improvements it provides in terms of segmentation accuracy

Coupled non-parametric shape and moment-based inter-shape pose priors for multiple basal ganglia structure segmentation

This paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We present a set of 2D and 3D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy

Multi-object segmentation using coupled nonparametric shape and relative pose priors

We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes

Çoklu beyin yapılarının bağlaşık, parametrik olmayan şekil önbilgisi kullanılarak bölütlenmesi = Segmentation of multiple brain structures using coupled nonparametric shape priors

We consider the problem of segmenting multiple brain structures in medical images. Due to the low contrast of medical images and the presence of noise, solution of this problem based only on image data, is rather challenging. Motivated by this observation, we propose an appraoch that incorporates prior information about the shapes of the anatomical structures, as well as about the interaction of neighboring shapes. We construct a statistical framework for the segmentation problem, which captures information about the shapes of coupled anatomical structures through prior probability density functions. We nonparametrically estimate these probability density functions from training shapes. We develop an active contour-based segmentation algorithm that combines image-based data with shape information. We demonstrate the benefits of our approach over existing methods through challenging segmentation scenarios on real magnetic resonance images

The frequency of Duchenne muscular dystrophy/Becker muscular dystrophy and Pompe disease in children with isolated transaminase elevation: results from the observational VICTORIA study

IntroductionElevated transaminases and/or creatine phosphokinase can indicate underlying muscle disease. Therefore, this study aims to determine the frequency of Duchenne muscular dystrophy/Becker muscular dystrophy (DMD/BMD) in male children and Pompe disease (PD) in male and female children with isolated hypertransaminasemia.MethodsThis multi-center, prospective study enrolled patients aged 3–216 months with serum alanine transaminase (ALT) and/or aspartate transaminase (AST) levels >2× the upper limit of normal (ULN) for ≥3 months. Patients with a known history of liver or muscle disease or physical examination findings suggestive of liver disease were excluded. Patients were screened for creatinine phosphokinase (CPK) levels, and molecular genetic tests for DMD/BMD in male patients and enzyme analysis for PD in male and female patients with elevated CPK levels were performed. Genetic analyses confirmed PD. Demographic, clinical, and laboratory characteristics of the patients were analyzed.ResultsOverall, 589 patients [66.8% male, mean age of 63.4 months (standard deviation: 60.5)] were included. In total, 251 patients (188 male and 63 female) had CPK levels above the ULN. Of the patients assessed, 47% (85/182) of male patients were diagnosed with DMD/BMD and 1% (3/228) of male and female patients were diagnosed with PD. The median ALT, AST, and CPK levels were statistically significantly higher, and the questioned neurological symptoms and previously unnoticed examination findings were more common in DMD/BMD patients than those without DMD/BMD or PD (p < 0.001).DiscussionQuestioning neurological symptoms, conducting a complete physical examination, and testing for CPK levels in patients with isolated hypertransaminasemia will prevent costly and time-consuming investigations for liver diseases and will lead to the diagnosis of occult neuromuscular diseases. Trial RegistrationClinicaltrials.gov NCT04120168