Does climate change affect bank lending behavior?

We examine how banks adjust credit supply in areas with higher exposure to climate risks by utilizing the province-level air pollution and loan growth data of a large emerging market, Turkey, following the Paris Agreement in 2015. Our results show that banks limit their credit extension to more polluted provinces in the post-agreement interval, implying that banks consider climate change-related risks and adjust their credit provisioning accordingly. Our baseline findings are intact against a myriad of robustness checks. We also find that the shift in the climate risk-credit provisioning nexus is asymmetric depending on the levels of air pollution.Publisher PDFPeer reviewe

Is Positron Emission Tomography Reliable to PredictPost-Chemotherapy Retroperitoneal Lymph NodeInvolvement in Advanced Germ Cell Tumors of theTestis?

PURPOSE: To evaluate if 18 fluorodeoxyglucose positron emission tomography(18FDG-PET) scan could identify post-chemotherapy retroperitoneal lymphnode (RPLN) involvement in advanced germ cell tumors of the testis.MATERIALS AND METHODS: Between January 2005 and January 2009, 16patients with advanced germ cell tumors of the testis underwent RPLNdissection (RPLND) following chemotherapy. Before RPLND, abdominalcomputed tomography (CT), magnetic resonance imaging (MRI), and18FDG-PET were performed in all the patients. Findings on 18FDG-PETwere compared with pathological evaluation of the removed lymphatic tissue.RESULTS: Both abdominal CT and MRI demonstrated retroperitonealmasses in all the patients following chemotherapy. Although PET did not demonstrate any activity in 8 patients, tumor was detected histopathologically.In 1 patient, 18FDG-PET demonstrated activity; however, no tumor wasdetected on pathology. Of the remaining 7 patients, 18FDG-PET findingswere concordant with the histopathological findings. No activity wasdetected in 2 patients with no tumors whereas all 5 patients harboring viabletumor cells showed positive 18FDG-PET activity. In our study, sensitivityand specificity of 18FDG-PET in detecting RPLN involvement were detectedto be 39% and 67%, respectively.CONCLUSION: 18FDG-PET imaging does not seem to be a reliable methodin detecting RPLN involvement in advanced germ cell tumors of the testisfollowing chemotherapy. Therefore, we neither recommend routine use of18FDG-PET scanning nor decide the treatment work-up by solely relying onthe 18FDG-PET findings in this patient group

Do Livestock Supports Increase Livestock Production? Province Based Panel ARDL Analysis for Turkey Example

In recent years, there has been a significant change in Turkey's agricultural support policies, especially on livestock supports. The livestock support, with a share less than 5% in total has in early 2000s has reached up to 35% at the end of 2020. In order to understand the impact of increase in livestock supports, 11 years of livestock support and livestock presence in 81 provinces in Turkey were analyzed via Panel ARDL method. The results of the analysis revealed that support to livestock does not affect the number of livestock in the short term, but has a positive effect in the long run. Furthermore, both in the short and long term, the increase in prices in the livestock sector increases the livestock fund. Eventhough increases in feed prices harm livestock presence in short run as expected, this negative effect disappears in the long run. The production effect of minimum wage variable is added to the model considering the unique situation of Turkey, which effects the production negative in the short run, but positive in the long run

The Effects of Trainings with Futsal Ball on Dribbling and Passing Skills on Youth Soccer Players

The aim of this study is to examine the effect of futsal balls on the passing and dribbling skills of 11-12 year old of soccer players. For this purpose, 48 male students whom regularly went to soccer school participated in the study. 24 of the students were in the control group (CG) and the other 24 were in the experimental group (EG). While the experimental group exercised with a futsal ball, the athletes in the control group continued their classical training program with a soccer ball. Experimental and control groups were planned to have a total of 24 sessions for 8 weeks, with 3 training sessions per week. The Mor-Christian General Soccer Ability Skill Test Battery (dribbling and passing) was used in the research. Statistical analyses were performed using the SPSS Windows 16.0 package program for the evaluation of the findings obtained in the study. Study results show that while both groups showed statistical improvement in passing skill in the pre and post tests (p<0,05), there wasn’t seen any improvement in dribbling skill (p>0,05).  However when we compared the improvements between groups, it was seen that EG players improved their passing skills better than CG players (p<0,05). In conclusion, it can be observed that the children who train with heavier and less bouncy futsal balls make contact with the ball more often and they become more focused, which results in an enhacement in their game skills and also has a positive effect on traditional soccer game

MSVD-Turkish: A comprehensive multimodal dataset for integrated vision and language research in Turkish

Automatic generation of video descriptions in natural language, also called video captioning, aims to understand the visual content of the video and produce a natural language sentence depicting the objects and actions in the scene. This challenging integrated vision and language problem, however, has been predominantly addressed for English. The lack of data and the linguistic properties of other languages limit the success of existing approaches for such languages. In this paper we target Turkish, a morphologically rich and agglutinative language that has very different properties compared to English. To do so, we create the first large scale video captioning dataset for this language by carefully translating the English descriptions of the videos in the MSVD (Microsoft Research Video Description Corpus) dataset into Turkish. In addition to enabling research in video captioning in Turkish, the parallel English-Turkish descriptions also enables the study of the role of video context in (multimodal) machine translation. In our experiments, we build models for both video captioning and multimodal machine translation and investigate the effect of different word segmentation approaches and different neural architectures to better address the properties of Turkish. We hope that the MSVD-Turkish dataset and the results reported in this work will lead to better video captioning and multimodal machine translation models for Turkish and other morphology rich and agglutinative languages

Cross-lingual Visual Pre-training for Multimodal Machine Translation

Supplements for the paper entitled "Cross-lingual Visual Pre-training for Multimodal Machine Translation" which is accepted by the EACL'2021 conference. Further instructions on how to use these resources are explained at https://github.com/ImperialNLP/VTLM A tarball that contains a custom train, valid, test split of Conceptual Captions (CC) dataset. The included TSV files havean additional column containing automatic German translations of the original English captions. We only provide samples for which we could download the images and extract meaningful features. This amounts to ~3M out ouf ~3.3M original CC samples. A tarball of the exact object detector checkpoint used for feature extraction. A tarball with pre-extracted Multi30k dataset features

Learning flat optics for extended depth of field microscopy imaging

International audienceConventional microscopy systems have limited depth of field, which often necessitates depth scanning techniques hindered by light scattering. Various techniques have been developed to address this challenge, but they have limited extended depth of field (EDOF) capabilities. To overcome this challenge, this study proposes an end-to-end optimization framework for building a computational EDOF microscope that combines a 4f microscopy optical setup incorporating a learned optics at the Fourier plane and a post-processing deblurring neural network. Utilizing the end-to-end differentiable model, we present a systematic design methodology for computational EDOF microscopy based on the specific visualization requirements of the sample under examination. In particular, we demonstrate that the metasurface optics provides key advantages for extreme EDOF imaging conditions, where the extended DOF range is well beyond what is demonstrated in state of the art, achieving superior EDOF performance