The role of vitamin D in the brain and related neurological diseases

Vitamin D is a steroid hormone that is produced photochemicallyin epidermis. It is known that vitamin D involvedin the regulation of bone mineralization and calcium-phosphorus balance. However, in recent studies havesuggested that vitamin D may have a significant impactin the development of the cell proliferation, differentiation,neurotransmission, neuroplasticity, neurotropic andneuroprotective effects in central nervous system (CNS).For the reason of the effects, it can be considered as aneurosteroid was reported. It was discussed that the levelof vitamin D may be associated to neurodegenerativediseases such as Parkinson’s disease, Alzheimer’s disease,multiple sclerosis (MS), amyotrophic lateral sclerosis(ALS). The role of vitamin D and the mechanisms ofthese diseases will be discussed in the review. J Clin ExpInvest 2013; 4 (3): 411-415Key words: Vitamin D, neurosteroid, brain, neurologicdisease

Probabilistic facial feature extraction using joint distribution of location and texture information

In this work, we propose a method which can extract critical points on a face using both location and texture information. This new approach can automatically learn feature information from training data. It finds the best facial feature locations by maximizing the joint distribution of location and texture parameters. We first introduce an independence assumption. Then, we improve upon this model by assuming dependence of location parameters but independence of texture parameters.We model combined location parameters with a multivariate Gaussian for computational reasons. The texture parameters are modeled with a Gaussian mixture model. It is shown that the new method outperforms active appearance models for the same experimental setup

A sliding mode approach to visual motion estimation

The problem of estimating motion from a sequence of images has been a major research theme in machine vision for many years and remains one of the most challenging ones. In this work, we use sliding mode observers to estimate the motion of a moving body with the aid of a CCD camera. We consider a variety of dynamical systems which arise in machine vision applications and develop a novel identication procedure for the estimation of both constant and time varying parameters. The basic procedure introduced for parameter estimation is to recast image feature dynamics linearly in terms of unknown parameters and construct a sliding mode observer to produce asymptotically correct estimates of the observed image features, and then use “equivalent control” to explicitly compute parameters. Much of our analysis has been substantiated by computer simulations and real experiments

A Determination of the Corrosion and Microstructure Properties of AlSi10Mg Material Produced by Different Direct Metal Laser Sintering (DMLS) Process Parameters

Additive Manufacturing (AM) has been developing with increasing interest recently. The development of this technology will accelerate with the increase in material, process, and product quality. It is therefore essential to investigate these shortcomings of additive manufacturing products. In this study, the microstructure and corrosion properties of the material (AlSi10Mg) were investigated by changing the production parameters in the Direct Metal Laser Sintering (DMLS) process. Energy density was considered in parameter selection. Depending on the process parameters, the corrosion, topography, and mechanical properties of the DMLSAlSi10Mg material were investigated in detail. It has been determined that the corrosion resistance and hardness of the material are directly related to porosity

Aligning digitalization and sustainability: Opportunities and challenges for corporate success and the achievement of sustainable development goals

Digitalization provides valuable benefts for entities and offers unique opportunities to strategically address challenges associated with the United Nations Sustainable Development Goals (SDGs) to ensure a sustainable society. This chapter discusses potential cross-fertilization effects between digitalization and sustainability to catalyze the benefts and challenges of digital transformation on the corporate level and SDGs’ perspective by focusing on sustainable practices. This chapter provides valuable insights for professionals and policymakers on the trends of digitalization and how they can support the SDGs that become a global compass for navigating sustainability challenges

Lip segmentation using adaptive color space training

In audio-visual speech recognition (AVSR), it is beneficial to use lip boundary information in addition to texture-dependent features. In this paper, we propose an automatic lip segmentation method that can be used in AVSR systems. The algorithm consists of the following steps: face detection, lip corners extraction, adaptive color space training for lip and non-lip regions using Gaussian mixture models (GMMs), and curve evolution using level-set formulation based on region and image gradients fields. Region-based fields are obtained using adapted GMM likelihoods. We have tested the proposed algorithm on a database (SU-TAV) of 100 facial images and obtained objective performance results by comparing automatic lip segmentations with hand-marked ground truth segmentations. Experimental results are promising and much work has to be done to improve the robustness of the proposed method

The effects of typical and atypical antipsychotics on the electrical activity of the brain in a rat model

Objective: Antipsychotic drugs are known to have strongeffect on the bioelectric activity in the brain. However,some studies addressing the changes on electroencephalography(EEG) caused by typical and atypical antipsychoticdrugs are conflicting. We aimed to compare the effectsof typical and atypical antipsychotics on the electricalactivity in the brain via EEG recordings in a rat model.Methods: Thirty-two Sprague Dawley adult male ratswere used in the study. The rats were divided into fivegroups, randomly (n=7, for each group). The first groupwas used as control group and administered 1 ml/kg salineintraperitoneally (IP). Haloperidol (1 mg/kg) (group 2),chlorpromazine (5 mg/kg) (group 3), olanzapine (1 mg/kg)(group 4), ziprasidone (1 mg/ kg) (group 5) were injectedIP for five consecutive days. Then, EEG recordings ofeach group were taken for 30 minutes.Results: The percentages of delta and theta waves inhaloperidol, chlorpromazine, olanzapine and ziprasidonegroups were found to have a highly significant differencecompared with the saline administration group (p<0.001).The theta waves in the olanzapine and ziprasidonegroups were increased compared with haloperidol andchlorpromazine groups (p<0.05).Conclusion: The typical and atypical antipsychotic drugsmay be risk factor for EEG abnormalities. This studyshows that antipsychotic drugs should be used with caution.J Clin Exp Invest 2013; 4 (3): 279-284Key words: Haloperidol, chlorpromazine, olanzapine,ziprasidone, EEG, ra

Melih Cevdet alkışlarla uğurlandı

Taha Toros Arşivi, Dosya No: 326-Melih Cevdet Andayİstanbul Kalkınma Ajansı (TR10/14/YEN/0033) İstanbul Development Agency (TR10/14/YEN/0033

Cerebral hemodynamics in patients with cirrhosis

Background/Aims: Cirrhosis causes a decrease in cerebral blood flow because of a hyperdynamic circulatory state. We aimed to study the cerebral hemodynamic parameters in patients with decompensated cirrhosis and their relationship to the Child-Pugh and Model for End-Stage Liver Disease (MELD) scores. Materials and Methods: We used transcranial Doppler to investigate the cerebral hemodynamic parameters, namely the mean flow velocity of the middle cerebral artery, pulsatility index (PI), and resistive index (RI), in 50 patients who had decompensated cirrhosis and in a control group of 50 healthy people. We also investigated their relationship to the Child-Pugh and MELD scores. Results: Patients with cirrhosis had a lower mean flow velocity than those in the control group. Further, patients with cirrhosis had higher PI and RI values. There was a positive correlation between PI and the Child-Pugh score. In addition, there was a positive correlation among PI, RI, and the MELD score. The RI values of patients with ascites were higher than those of patients without ascites. Conclusion: Cerebral autoregulation might be impaired in patients with cirrhosis. Cerebral resistance proportionally increases to disease severity. There was a positive correlation among PI, RI, and MELD scores, which means that transcranial Doppler might be useful not only in the follow-up of the severity of the disease but also in determining the survival of these patients. © Copyright 2016 by The Turkish Society of Gastroenterology

Offline signature verification using classifier combination of HOG and LBP features

We present an offline signature verification system based on a signature’s local histogram features. The signature is divided into zones using both the Cartesian and polar coordinate systems and two different histogram features are calculated for each zone: histogram of oriented gradients (HOG) and histogram of local binary patterns (LBP). The classification is performed using Support Vector Machines (SVMs), where two different approaches for training are investigated, namely global and user-dependent SVMs. User-dependent SVMs, trained separately for each user, learn to differentiate a user’s signature from others, whereas a single global SVM trained with difference vectors of query and reference signatures’ features of all users, learns how to weight dissimilarities. The global SVM classifier is trained using genuine and forgery signatures of subjects that are excluded from the test set, while userdependent SVMs are separately trained for each subject using genuine and random forgeries. The fusion of all classifiers (global and user-dependent classifiers trained with each feature type), achieves a 15.41% equal error rate in skilled forgery test, in the GPDS-160 signature database without using any skilled forgeries in training