Exchange rates and fundamentals: is there a role for nonlinearities in real time?

We examine the predictive power of real time linear monetary models with possible nonlinear adjustment in forecast errors for the GBP/USD exchange rates. Real time revisions of UK and US monetary aggregates and output are significant; therefore the use of final data on fundamentals in forecasting exchange rates may yield misleading inferences. By studying recursive forecast errors we claim that in several instances, real time fundamental equilibrium values of exchange rates may be determined in a linear fashion, whereas the adjustment towards fundamentals driven equilibrium values may take a discrete or smooth nonlinear form. Revisions in fundamentals, particularly in the US and UK monetary aggregates and real output, seem to matter mainly for short term forecastability of exchange rates. We find short term forecastability in the form of discrete nonlinear adjustment in some real time vintages. We also document long term forecastability in the form of a smooth nonlinear adjustment towards fundamentals determined equilibrium values of exchange rates

Automatic detection and segmentation of orchards using very high-resolution imagery

Cataloged from PDF version of article.Spectral information alone is often not sufficient to distinguish certain terrain classes such as permanent crops like orchards, vineyards, and olive groves from other types of vegetation. However, instances of these classes possess distinctive spatial structures that can be observable in detail in very high spatial resolution images. This paper proposes a novel unsupervised algorithm for the detection and segmentation of orchards. The detection step uses a texture model that is based on the idea that textures are made up of primitives (trees) appearing in a near-regular repetitive arrangement (planting patterns). The algorithm starts with the enhancement of potential tree locations by using multi-granularity isotropic filters. Then, the regularity of the planting patterns is quantified using projection profiles of the filter responses at multiple orientations. The result is a regularity score at each pixel for each granularity and orientation. Finally, the segmentation step iteratively merges neighboring pixels and regions belonging to similar planting patterns according to the similarities of their regularity scores and obtains the boundaries of individual orchards along with estimates of their granularities and orientations. Extensive experiments using Ikonos and QuickBird imagery as well as images taken from Google Earth show that the proposed algorithm provides good localization of the target objects even when no sharp boundaries exist in the image data. © 2012 IEEE

Call and Response: SEM President’s Roundtable 2016, “Ethnomusicological Responses to the Contemporary Dynamics of Migrants and Refugees”

The privilege of organizing the SEM President’s Roundtable in 2016 and 2017 provided an opportunity to call attention to a topic that has concerned my teaching and research since graduate school. For the first iteration of “Ethnomusicological Responses to the Contemporary Dynamics of Migrants and Refugees” I convened a panel of people whose perspectives I admire. I wanted to learn from them, and I did. As someone who has been involved with Middle Eastern and more specifically Arab music and culture within my own academic and regional community, I was making new efforts in the fall of 2016 toward engaged ethnomusicology in Virginia among my own newest neighbors, and organizing this SEM President’s Roundtable gave me courage and inspiration. Our “Call and Response” presents snapshots from five colleagues who are engaged with communities of migrants and refugees in Africa, the Middle East, Europe, and North America..

Assessment of paranasal sinus parameters according to ancient skulls’ gender and age by using cone-beam computed tomography

Background: The aim of this study was to determine whether paranasal sinus dimensions and volume can be useful to identify gender and age estimation for ancient skulls using cone-beam computed tomography (CBCT) images.  Materials and methods: CBCT scans of 32 ancient skulls of approximately 1000 years of age were included in this retrospective study. The gender and age estimation of the skulls were made by an independent anthropologist, which was considered as the gold standard. Paranasal sinuses’ dimensions (width and height) and volumes of each sinus were measured from the CBCT data set that was linked to the three-dimensional rendering software (Anatomage, Invivo 5.2). All measurements were performed by an independent observer. Intra-observer analysis was made. Mann-Whitney and Kruskal-Wallis tests were used to compare paranasal sinus parameters in terms of age estimation and gender (p < 0.05).  Results: The results demonstrated no statistically significant difference between measurements (p < 0.05). The measurements were found to be highly reprodu- cible. The mean volumes of frontal and sphenoid sinus were found to be higher in males. The distance from anterior-posterior wall of sphenoid sinus in axial sec- tions is larger in males (p > 0.05). The frontal sinus width and volume increased statistically with age above 60 years of age (p > 0.05).  Conclusions: The paranasal volume and dimensions’ measurements from CBCT data can be a promising technique to determine gender and age of ancient skulls because of its lower voxel sizes and higher resolution.

Untangling the influence of corporate sustainability on export intensity : the moderating role of R&D intensity

Growing global environmental and social issues have imposed increased pressure on firms to address sustainability challenges in international markets, with a particular focus on improving their export performance. This is of significant importance for emerging market firms aiming to expand their presence in international markets, as they are compelled to bolster their environmental and social sustainability capacity to enhance their export intensity. This study delves into the relationship between corporate sustainability and export intensity through a longitudinal examination of 141 firms listed on Borsa Istanbul from 2014 to 2021. The results suggest that corporate sustainability positively influences export intensity, and this influence is further positively moderated by R&D intensity. Additionally, post-hoc analysis employing supplementary data pertaining to the environmental, social, and governance dimensions of corporate sustainability reveals that environmental performance plays a positive role in shaping export intensity, with R&D intensity positively moderating this relationship. In summary, our findings underscore that exporting firms that effectively integrate impactful R&D intensity into their international business operations are likely to harness their sustainability strategies, particularly those related to the natural environment, to achieve higher export intensity.© American Marketing Association 2023. The article is protected by copyright and reuse is restricted to non-commercial and no derivative uses. Users may also download and save a local copy of an article accessed in an institutional repository for the user's personal reference.fi=vertaisarvioitu|en=peerReviewed

Treatment trends for muscle-invasive bladder cancer in Germany from 2006 to 2019

Purpose: To examine national treatment trends of muscle-invasive bladder cancer (MIBC) in Germany with a special focus on radical cystectomy (RC). Patients and methods: Population-based data were derived from the nationwide hospital billing database of the German Federal Statistical Office and institution-related information from the reimbursement.INFO tool based on hospitals’ quality reports from 2006 to 2019. Additionally, we used the German National Center for Cancer Registry data to analyze all cases of bladder cancer with stage ≥ T2 who received RC, chemotherapy, radiation therapy or a combination from 2006 to 2017. Results: The annual number of RC cases in Germany increased by 28% from 5627 cases in 2006 to 7292 cases in 2019 (p = 0.001). The proportion of patients undergoing RC remained constant at about 75% in all age groups between 2006 and 2017 (p = 0.3). Relative to all performed RC, the proportion of patients > 75 years increased from 25% in 2006 to 38% in 2019 (p = 0.03). The proportion of patients receiving a combination of RC and chemotherapy increased from 9% in 2006 to 13% in 2017 (p = 0.005). In 2006, 8 of 299 urology departments (2.7%) performed more than 50 RCs per year, which increased to 17 of 360 (4.7%) in 2019. In 2019, 107 departments (29%) performed 25–49 RCs and 236 (66%) departments performed < 25 RCs. Conclusion: In Germany, three out of four patients with MIBC receive RC and the proportion of patients > 75 years is increasing. The combination of surgery and chemotherapy is increasingly used. With overall increasing case numbers, there is a slight tendency towards centralization.Peer Reviewe

The effect of anesthesia type on stress hormone response: Comparison of general versus epidural anesthesia

Aim: The aim of this study was to investigate the effect of different types of anesthesia on stress hormones.Materials and Methods: The study was included 60 ASAI-II cases scheduled for major lower extremity surgery. The cases were randomized into 2  groups: The EA group was administered epidural anesthesia and the GA group was administered standard general anesthesia. In order to evaluate the surgical trauma - related stress response, CRP, TSH, cortisol, and fasting blood sugar(FBS) levels were measured preoperatively, 30 min after surgical incision, and 24 h post surgery.Results: Between-group comparisons; Preoperative values were not  significantly different between the groups.(P &gt; 0,05) Pulse rate and cortisol values significantly higher in general group at 30 min. (P &lt; 0,05), and the FBS values were significantly higher in the epidural group at 24 h.(P &lt; 0,05) There were not found differences for other parameters at evaluation times.Conclusion: No differences were observed between the two anesthesia methods, in terms of minimizing the stress response due to surgical trauma during major low extremity surgery.Key words: Epidural anesthesia, general anesthesia, stress hormone

Interactive training of advanced classifiers for mining remote sensing image archives

Advances in satellite technology and availability of down-loaded images constantly increase the sizes of remote sensing image archives. Automatic content extraction, classification and content-based retrieval have become highly desired goals for the development of intelligent remote sensing databases. The common approach for mining these databases uses rules created by analysts. However, incorporating GIS information and human expert knowledge with digital image processing improves remote sensing image analysis. We developed a system that uses decision tree classifiers for interactive learning of land cover models and mining of image archives. Decision trees provide a promising solution for this problem because they can operate on both numerical (continuous) and categorical (discrete) data sources, and they do not require any assumptions about neither the distributions nor the independence of attribute values. This is especially important for the fusion of measurements from different sources like spectral data, DEM data and other ancillary GIS data. Furthermore, using surrogate splits provides the capability of dealing with missing data during both training and classification, and enables handling instrument malfunctions or the cases where one or more measurements do not exist for some locations. Quantitative and qualitative performance evaluation showed that decision trees provide powerful tools for modeling both pixel and region contents of images and mining of remote sensing image archives

Land cover classification with multi-sensor fusion of partly missing data

We describe a system that uses decision tree-based tools for seamless acquisition of knowledge for classification of remotely sensed imagery. We concentrate on three important problems in this process: information fusion, model understandability, and handling of missing data. Importance of multi-sensor information fusion and the use of decision tree classifiers for such problems have been well-studied in the literature. However, these studies have been limited to the cases where all data sources have a full coverage for the scene under consideration. Our contribution in this paper is to show how decision tree classifiers can be learned with alternative (surrogate) decision nodes and result in models that are capable of dealing with missing data during both training and classification to handle cases where one or more measurements do not exist for some locations. We present detailed performance evaluation regarding the effectiveness of these classifiers for information fusion and feature selection, and study three different methods for handling missing data in comparative experiments. The results show that surrogate decisions incorporated into decision tree classifiers provide powerful models for fusing information from different data layers while being robust to missing data. © 2009 American Society for Photogrammetry and Remote Sensing