A Hybrid Framework for Sequential Data Prediction with End-to-End Optimization

We investigate nonlinear prediction in an online setting and introduce a hybrid model that effectively mitigates, via an end-to-end architecture, the need for hand-designed features and manual model selection issues of conventional nonlinear prediction/regression methods. In particular, we use recursive structures to extract features from sequential signals, while preserving the state information, i.e., the history, and boosted decision trees to produce the final output. The connection is in an end-to-end fashion and we jointly optimize the whole architecture using stochastic gradient descent, for which we also provide the backward pass update equations. In particular, we employ a recurrent neural network (LSTM) for adaptive feature extraction from sequential data and a gradient boosting machinery (soft GBDT) for effective supervised regression. Our framework is generic so that one can use other deep learning architectures for feature extraction (such as RNNs and GRUs) and machine learning algorithms for decision making as long as they are differentiable. We demonstrate the learning behavior of our algorithm on synthetic data and the significant performance improvements over the conventional methods over various real life datasets. Furthermore, we openly share the source code of the proposed method to facilitate further research

The role of desire thinking in the problematic use of social networking sites among adults.

The problematic use of social networking sites (SNS) is associated with several psychiatric disorders. This behavior closely resembles addiction in terms of neurological basis and behavioral patterns. Nevertheless, successful intervention strategies and the etiology of problematic SNS use are not yet thoroughly investigated. We aimed to study whether desire thinking is associated with problematic SNS use among adults when controlling for some confounders, including boredom, affect, and impulsivity. With the help of convenience sampling, we enrolled 546 Turkish adults in this study to whom we administered a sociodemographic form, the Social Media Addiction Scale (SMAS), the Leisure Boredom Scale (LBS), the Positive and Negative Affect Schedule (PANAS), the Barratt Impulsiveness Scale (BIS-11), and the Desire Thinking Questionnaire (DTQ). To explore the association between the variables, we performed Pearson correlational and hierarchical regression analyses. The results showed that higher scores on two sub-dimensions of desire thinking, namely verbal perseveration and imaginal prefiguration, were associated with higher scores on problematic SNS use after we controlled for boredom, affect, and impulsivity. This study demonstrates that desire thinking may play a role in problematic SNS use among adults. We recommend targeting desire thinking as a potential area in treatments which may help alleviate problematic SNS use. [Abstract copyright: © 2022 The Authors. Published by Elsevier Ltd.

Hybrid State Space-based Learning for Sequential Data Prediction with Joint Optimization

We investigate nonlinear prediction/regression in an online setting and introduce a hybrid model that effectively mitigates, via a joint mechanism through a state space formulation, the need for domain-specific feature engineering issues of conventional nonlinear prediction models and achieves an efficient mix of nonlinear and linear components. In particular, we use recursive structures to extract features from raw sequential sequences and a traditional linear time series model to deal with the intricacies of the sequential data, e.g., seasonality, trends. The state-of-the-art ensemble or hybrid models typically train the base models in a disjoint manner, which is not only time consuming but also sub-optimal due to the separation of modeling or independent training. In contrast, as the first time in the literature, we jointly optimize an enhanced recurrent neural network (LSTM) for automatic feature extraction from raw data and an ARMA-family time series model (SARIMAX) for effectively addressing peculiarities associated with time series data. We achieve this by introducing novel state space representations for the base models, which are then combined to provide a full state space representation of the hybrid or the ensemble. Hence, we are able to jointly optimize both models in a single pass via particle filtering, for which we also provide the update equations. The introduced architecture is generic so that one can use other recurrent architectures, e.g., GRUs, traditional time series-specific models, e.g., ETS or other optimization methods, e.g., EKF, UKF. Due to such novel combination and joint optimization, we demonstrate significant improvements in widely publicized real life competition datasets. We also openly share our code for further research and replicability of our results.Comment: Submitted to the IEEE TNNLS journa

Turkish Accession and Defining the Boundaries of Nationalism and Supranationalism: Discourses in the European Commission

The European Union in general and the European Commission in particular are characterised by supranational governance. The enlargement policy gives the Commission the opportunity to export and promote supranational norms and define the boundaries of Europe as a supranational polity through the conditionality of membership and intensive contact with the candidate countries. This article analyses the discourses of the Commission on Turkey and gives us insights into how well Turkey fits the supranational model in the eyes of Commission officials. It demonstrates how the boundaries of supranationalism are set and even challenged by the prospects of Turkey’s accession

A review of \u3cem\u3eOrthochirus\u3c/em\u3e from Turkey, Iraq, and Iran (Khoozestan, Ilam, and Lorestan Provinces), with descriptions of three new species (Scorpiones: Buthidae)

Three new species, Orthochirus fomichevi sp. n. from Turkey and Iraq, O. gantenbeini sp. n. from Iran (Khoozestan Province), and O. navidpouri sp. n. from Iran (Khoozestan and Lorestan Provinces) are described, compared with other Orthochirus species from the region, and fully illustrated with color photos. Lectotype of O. mesopotamicus Birula, 1918 stat. n. from Iran (Khoozestan Province) is designated. Emended diagnoses are given for O. iranus Kovařík, 2004, O. iraqus Kovařík, 2004, O. mesopotamicus Birula, 1918 stat. n., and O. zagrosensis Kovařík, 2004. A key and a distribution map are included

Promoter methylation analysis of CDH1 and p14ARF genes in patients with urothelial bladder cancer

BACKGROUND/AIM: Urothelial bladder cancer arises from the accumulation of multiple epigenetic and genetic changes. We aimed to investigate the specificity and sensitivity of gene-specific promoter methylation of CDH1 and p14ARF genes in the early diagnosis of bladder cancer and compare those with other diagnostic tests in our population. PATIENTS AND METHODS: In the current study, 65 patients with urothelial bladder cancer and 35 controls without any history of cancer were recruited. Methylation profiles of CDH1 and p14ARF genes from tumor and urine samples were determined by methylation-specific polymerase chain reaction method. RESULTS: Methylation of CDH1 and p14ARF genes in tumor samples was 95.4% and 78.5%, respectively. The methylation frequencies were found to be 68.8% for CDH1 gene and 72.9% for p14ARF gene in urine samples. Sensitivities of CDH1, p14ARF and urine cytology were found to be 67.4%, 72.1% and 34.9%, respectively, while their specificities were 93.9%, 63.6% and 93.9%, respectively. CONCLUSION: Aberrant promoter methylation of CDH1 and p14ARF genes can be used to detect urothelial bladder cancer. In low-grade tumors, when compared with urine cytology, combined methylation analysis of CDH1 and p14ARF genes may not increase the sensitivity to identify malignant cells in urine samples

Children's Foreign Language Anxiety Scale: Preliminary Tests of Reliability and Validity

Foreign language anxiety (FLA), which constitutes a serious problem in the foreign language learning process, has been mainly seen as a research issue regarding adult language learners, while it has been overlooked in children. This is because there is a lack of appropriate tools to measure FLA among children, whereas there are many studies on the scales that aim to measure anxiety levels among adult learners. Thus, the current study aims to conduct the preliminary tests of reliability and validity of the Children's Foreign Language Anxiety Scale (CFLAS) and to report on the pilot examination of reliability, validity and factor structure of the CFLAS. The findings of the pilot study show that CFLAS is a reliable and valid tool to measure FLA levels among children who learn English as a foreign language (EFL) within the age range of 7-12 in a Turkish EFL context

Effects of salicylic acid on wheat salt sensitivity

Salicylic acid (SA), a plant phenolic compound, is now considered as a hormone-like endogenous regulator, and there is a great interest to clarify its role in the defence mechanisms against biotic and abiotic stressors. In this study, investigations on the effects of foliar-applied SA on salt sensitivity, hydrogen peroxide (H2O2) generation and activities of antioxidant enzymes like peroxidase (POX) and catalase (CAT) in plant tissues under salt stress was performed. SA treatment significantly increased the fresh and dry weights in both root and shoots of wheat plants under salt stress. Similarly, POX and CAT activities were also augmented by SA treatment. While the highest POX activity was recorded at SA+120 mM NaCl, CAT activity also exhibited an increase compared to salt treatment without SA. In parallel to increasing antioxidative activity, SA treatment decreased H2O2 content when compared to plants growing under salt stress without SA. The results revealed that salt-induced deleterious effect in wheat seedlings were significantly alleviated by the SA treatment. SA can be used as a signal molecule to investigate plant defense to abiotic stress. After the application of SA, increasing tolerance of wheat seedlings to salt stress may be related to increases in antioxidative enzyme activitiy.Key words: Wheat, salicylic acid, antioxidative enzyme activities, peroxidase (POX), catalase (CAT), hydrogen peroxide (H2O2) content