IMPACT ASSESSMENT ON MILK INCENTIVE POLICIES IN TURKEY: ANTALYA PROVINCE CASE

Agricultural policy instruments are implementing in different ways among all agricultural based activities. These instruments have been performed for livestock including dairy cattle and milk for many years in Turkey. Until the year 1950, agricultural support system was organized according to genetically improvement, animal illnesses and veterinary services. Nowadays, agricultural support composition has changed. Milk incentive premium is one of the supports given to producers to achieve high quality level for milk. The idea behind this premium was to provide well organized milk distribution channel from producers to modern enterprises. In this study, producers who receive milk incentive premium were chosen for face to face survey in Antalya province. It was examined from the study if premium system is accomplished through the idea. The secondary outcomes of the research were to determine the influence of the premium on producers attitudes, income level, product quantity, as well as membership tendency for cooperatives or unions.milk incentive premium, milk marketing, producer surplus, Antalya, Agricultural and Food Policy, Livestock Production/Industries,

Cointegration analysis of wine export prices for France, Greece and Turkey

Mediterranean countries have noticeable affect on the world wine exportation. Among these countries France, Greece and Turkey are selected for this study because of different wine market, trade systems and wine policies they have. In this study, cointegration analysis was conducted for real wine export prices and real exchange rates for France, Greece and Turkey. The long term relationships between real exchange rates and real wine export values were explored by using cointegration analysis. Annual data from 1970 to 2003 was used for this analysis and the data sets were found to be integrated of the same order. It was also found that they move together in the long run by Johansen Cointegration Test. Then, Error Correction Model (ECM) was applied to search any short term relations and impacts of exchange rate variations on wine exports. French and Greek monetary policies affect their wine export volume by the years. Therefore, any depreciation of local currency in dollar terms will lead to increase of exports vice versa. On the other hand, Turkish wine real export value and real exchange rate were found not cointegrated. Since, there was not any cointegrated vector, any exchange rate volatility do not influence Turkish real export wine value. Subsequently, the reasons of wine market failures in these countries and pursued policies were discussed.Cointegration Analysis, Error Correction Model (ECM), Wine Export Prices, Real Exchange Rates, Wine Market, Demand and Price Analysis,

Multislice/multidetector-row computed tomography findings of a rare coronary anomaly: the first septal perforator branch originating from the left main coronary artery

Multislice/multidetector-row computed tomography (MDCT) is now widely used for noninvasive assessment of coronary arteries, and it may sometimes reveal coronary anomalies. Detection of such anomalies may be relevant both during follow-up and for planning cardiac or coronary surgical/interventional procedures. These anomalies may be missed unless carefully sought. In this paper, we present the MDCT images of a first septal perforator branch originating from the left main coronary artery, which represents an extremely rare coronary anomaly. To the bestof our knowledge, this is the first case in the literature where MDCT images are presented

Putting Security on the Table: The Digitalisation of Security Tabletop Games and its Challenging Aftertaste

IT-Security Tabletop Games for developers have been available in analog format; with the COVID-19 pandemic, interest in collaborative remote security games has increased. In this paper, we propose a methodology to evaluate the impact of a (remote) security game-based intervention on developers. The study design consists of the respective intervention, three questionnaires, and a small open interview guide for a focus group. A validated self-efficacy scale is used as a proxy for measuring effects on participants' ability to develop secure software. We tested this design with 9 participants (expert and novice developers and security experts) as part of a small feasibility study to understand the challenges and limitations of remote tabletop games. We describe how we selected and digitalised three security tabletop games, and report the qualitative findings from our evaluation. Setting up and running the virtual tabletop games turned out to be more challenging and complex for both moderator and participants than we expected. Completing the games required patience and persistence, and social interaction was limited. Our findings can be helpful in building and evaluating a better, more comprehensive, technically sound and issue-specific game-based training measure for developers. The methodology can be used by researchers to evaluate existing and new game designs

The Krylov-proportionate normalized least mean fourth approach: Formulation and performance analysis

Cataloged from PDF version of article.We propose novel adaptive filtering algorithms based on the mean-fourth error objective while providing further improvements on the convergence performance through proportionate update. We exploit the sparsity of the system in the mean-fourth error framework through the proportionate normalized least mean fourth (PNLMF) algorithm. In order to broaden the applicability of the PNLMF algorithm to dispersive (non-sparse) systems, we introduce the Krylov-proportionate normalized least mean fourth (KPNLMF) algorithm using the Krylov subspace projection technique. We propose the Krylov-proportionate normalized least mean mixed norm (KPNLMMN) algorithm combining the mean-square and mean-fourth error objectives in order to enhance the performance of the constituent filters. Additionally, we propose the stable-PNLMF and stable-KPNLMF algorithms overcoming the stability issues induced due to the usage of the mean fourth error framework. Finally, we provide a complete performance analysis, i.e., the transient and the steady-state analyses, for the proportionate update based algorithms, e.g., the PNLMF, the KPNLMF algorithms and their variants; and analyze their tracking performance in a non-stationary environment. Through the numerical examples, we demonstrate the match of the theoretical and ensemble averaged results and show the superior performance of the introduced algorithms in different scenarios. (C) 2014 Elsevier B.V. All rights reserved

A Neural Circuit Arbitrates between Persistence and Withdrawal in Hungry Drosophila

In pursuit of food, hungry animals mobilize significant energy resources and overcome exhaustion and fear. How need and motivation control the decision to continue or change behavior is not understood. Using a single fly treadmill, we show that hungry flies persistently track a food odor and increase their effort over repeated trials in the absence of reward suggesting that need dominates negative experience. We further show that odor tracking is regulated by two mushroom body output neurons (MBONs) connecting the MB to the lateral horn. These MBONs, together with dopaminergic neurons and Dop1R2 signaling, control behavioral persistence. Conversely, an octopaminergic neuron, VPM4, which directly innervates one of the MBONs, acts as a brake on odor tracking by connecting feeding and olfaction. Together, our data suggest a function for the MB in internal state-dependent expression of behavior that can be suppressed by external inputs conveying a competing behavioral drive

DeepSym: Deep Symbol Generation and Rule Learning from Unsupervised Continuous Robot Interaction for Planning

Autonomous discovery of discrete symbols and rules from continuous interaction experience is a crucial building block of robot AI, but remains a challenging problem. Solving it will overcome the limitations in scalability, flexibility, and robustness of manually-designed symbols and rules, and will constitute a substantial advance towards autonomous robots that can learn and reason at abstract levels in open-ended environments. Towards this goal, we propose a novel and general method that finds action-grounded, discrete object and effect categories and builds probabilistic rules over them that can be used in complex action planning. Our robot interacts with single and multiple objects using a given action repertoire and observes the effects created in the environment. In order to form action-grounded object, effect, and relational categories, we employ a binarized bottleneck layer of a predictive, deep encoder-decoder network that takes as input the image of the scene and the action applied, and generates the resulting object displacements in the scene (action effects) in pixel coordinates. The binary latent vector represents a learned, action-driven categorization of objects. To distill the knowledge represented by the neural network into rules useful for symbolic reasoning, we train a decision tree to reproduce its decoder function. From its branches we extract probabilistic rules and represent them in PPDDL, allowing off-the-shelf planners to operate on the robot's sensorimotor experience. Our system is verified in a physics-based 3d simulation environment where a robot arm-hand system learned symbols that can be interpreted as 'rollable', 'insertable', 'larger-than' from its push and stack actions; and generated effective plans to achieve goals such as building towers from given cubes, balls, and cups using off-the-shelf probabilistic planners

Evolved bacterial resistance against fluoropyrimidines can lower chemotherapy impact in the Caenorhabditis elegans host

Metabolism of host-targeted drugs by the microbiome can substantially impact host treatment success. However, since many host-targeted drugs inadvertently hamper microbiome growth, repeated drug administration can lead to microbiome evolutionary adaptation. We tested if evolved bacterial resistance against host-targeted drugs alters their drug metabolism and impacts host treatment success. We used a model system of Caenorhabditis elegans, its bacterial diet, and two fluoropyrimidine chemotherapies. Genetic screens revealed that most of loss-of-function resistance mutations in Escherichia coli also reduced drug toxicity in the host. We found that resistance rapidly emerged in E. coli under natural selection and converged to a handful of resistance mechanisms. Surprisingly, we discovered that nutrient availability during bacterial evolution dictated the dietary effect on the host - only bacteria evolving in nutrient-poor media reduced host drug toxicity. Our work suggests that bacteria can rapidly adapt to host-targeted drugs and by doing so may also impact the host

Salt inducible kinases as novel Notch interactors in the developing Drosophila retina

Developmental processes require strict regulation of proliferation, differentiation and patterning for the generation of final organ size. Aberrations in these fundamental events are critically important in tumorigenesis and cancer progression. Salt inducible kinases (Siks) are evolutionarily conserved genes involved in diverse biological processes, including salt sensing, metabolism, muscle, cartilage and bone formation, but their role in development remains largely unknown. Recent findings implicate Siks in mitotic control, and in both tumor suppression and progression. Using a tumor model in the Drosophila eye, we show that perturbation of Sik function exacerbates tumor-like tissue overgrowth and metastasis. Furthermore, we show that both Drosophila Sik genes, Sik2 and Sik3, function in eye development processes. We propose that an important target of Siks may be the Notch signaling pathway, as we demonstrate genetic interaction between Siks and Notch pathway members. Finally, we investigate Sik expression in the developing retina and show that Sik2 is expressed in all photoreceptors, basal to cell junctions, while Sik3 appears to be expressed specifically in R3/R4 cells in the developing eye. Combined, our data suggest that Sik genes are important for eye tissue specification and growth, and that their dysregulation may contribute to tumor formation