Chatbots talk Strabismus: Can AI become the new patient Educator?

Background: Strabismus is a common eye condition affecting both children and adults. Effective patient education is crucial for informed decision-making, but traditional methods often lack accessibility and engagement. Chatbots powered by AI have emerged as a promising solution. Aim: This study aims to evaluate and compare the performance of three chatbots (ChatGPT, Bard, and Copilot) and a reliable website (AAPOS) in answering real patient questions about strabismus. Method: Three chatbots (ChatGPT, Bard, and Copilot) were compared to a reliable website (AAPOS) using real patient questions. Metrics included accuracy (SOLO taxonomy), understandability/actionability (PEMAT), and readability (Flesch-Kincaid). We also performed a sentiment analysis to capture the emotional tone and impact of the responses. Results: The AAPOS achieved the highest mean SOLO score (4.14 ± 0.47), followed by Bard, Copilot, and ChatGPT. Bard scored highest on both PEMAT-U (74.8 ± 13.3) and PEMAT-A (66.2 ± 13.6) measures. Flesch-Kincaid Ease Scores revealed the AAPOS as the easiest to read (mean score: 55.8 ± 14.11), closely followed by Copilot. ChatGPT, and Bard had lower scores on readability. The sentiment analysis revealed exciting differences. Conclusion: Chatbots, particularly Bard and Copilot, show promise in patient education for strabismus with strengths in understandability and actionability. However, the AAPOS website outperformed in accuracy and readability. © 2024 Elsevier B.V

Pre-Service Turkish and English Teachers’ Achievement Levels, Perceptions of Self-Efficacy and Attitudes in relation to Summarizing Skills

This study aims to compare pre-service Turkish and English teachers’ achievement levels, perceptions of self-efficacy and attitudes in relation to summarizing skills. This study adopted a sequential mixed method research design and there were 265 pre-service teachers who were chosen via convenience sampling. The data were obtained via a story summary rubric, the summarizing attitude scale, summarizing self-efficacy perception scale and a semi-structured interview form. While the quantitative data were analyzed by statistical methods, the qualitative data were subjected to summative content analysis. According to the findings, summarizing achievement level of the participants was at a good level. Also, it was found that the participants had a high level of belief in the importance of summarizing, they enjoyed summarizing at a moderate level, and their attitude scores towards summarizing were high. In addition, the participants' summary-based reading, summary writing and self-efficacy perceptions of summarizing were at a high level. On the other hand, it was revealed that there were no significant differences between the scores of the pre-service English and Turkish teachers in terms of summarizing achievement levels, believing in the importance of summarizing, reading for summarizing, writing summary and summarizing self-efficacy. Finally, there was a significant difference in favor of the pre-service Turkish teachers in the dimension of enjoying summarizing and the overall scores of the summarizing attitudes scale

Automated Classification System Based on YOLO Architecture for Body Condition Score in Dairy Cows

Simple Summary This study proposes an automatic classification system for determining body condition score in dairy cows using a deep learning architecture. An original dataset was created by categorizing images of different breeds from different farms into five body condition score classes: Emaciated, Poor, Good, Fat, and Obese. In the experimental analysis, the proposed deep learning model accurately classified 102 out of 126 cow images in the test set, achieving an average accuracy of 0.81 for all classes in Holstein and Simmental cows and an average area under the precision-recall curve of 0.87. The proposed body condition score classification system can help to accurately monitor rapid declines in body condition in dairy cows and serve as a tool for production decision-makers to reduce negative energy balance during early lactation.Abstract Body condition score (BCS) is a common tool used to assess the welfare of dairy cows and is based on scoring animals according to their external appearance. If the BCS of dairy cows deviates from the required value, it can lead to diseases caused by metabolic problems in the animal, increased medication costs, low productivity, and even the loss of dairy cows. BCS scores for dairy cows on farms are mostly determined by observation based on expert knowledge and experience. This study proposes an automatic classification system for BCS determination in dairy cows using the YOLOv8x deep learning architecture. In this study, firstly, an original dataset was prepared by dividing the BCS scale into five different classes of Emaciated, Poor, Good, Fat, and Obese for images of Holstein and Simmental cow breeds collected from different farms. In the experimental analyses performed on the dataset prepared in this study, the BCS values of 102 out of a total of 126 cow images in the test set were correctly classified using the proposed YOLOv8x deep learning architecture. Furthermore, an average accuracy of 0.81 was achieved for all BCS classes in Holstein and Simmental cows. In addition, the average area under the precision-recall curve was 0.87. In conclusion, the BCS classification system for dairy cows proposed in this study may allow for the accurate observation of animals with rapid declines in body condition. In addition, the BCS classification system can be used as a tool for production decision-makers in early lactation to reduce the negative energy balance

Leaf blight caused by Didymella glomerata on blackberry in Turkey

The cultivation of blackberries has recently increased in Turkey, despite the fact that wild blackberry types have grown almost everywhere in the country. During the summer of 2011, leaf blight symptoms were observed in a blackberry vineyard in Karlisu, as well as on wild blackberry plants in Altinozu, Hatay province, Turkey. Based on morphology, fungal isolates obtained from these blighted leaf margins shared similar morphological characteristics and were tentatively identified as Didymella glomerata. To confirm the morphologic identification, the nucleotide sequences of a representative isolate's ITS, LSU, and tub2 regions of DNA were used. The sequences of three regions were 99-100% identical to D. glomerata isolate sequences in GenBank. Healthy blackberry suckers of the thornless blackberry cultivars 'Triple Crown' and 'Chester' grown in pots were inoculated with spore suspension on foliar parts under greenhouse conditions for pathogenicity testing. D. glomerata was extremely virulent, causing severe leaf blight in both blackberry cultivars. D. glomerata was constantly isolated from inoculated plants' leaf lesions. This is the first report of D. glomerata infection of blackberry, a novel host for this pathogen in Turkey and around the world. More research into the biology and management of the disease is required.Mardin Artuklu University [MAU.BAP.18]This work was partially supported by the Mardin Artuklu University Grant Number [MAU.BAP.18.KMYO.044]

A SEARCH FOR LEPTONIC PHOTON, Z l , AT ALL THREE CLIC ENERGY STAGES BY USING ARTIFICIAL NEURAL NETWORKS (ANN)

In this work, the possible dynamics of the massive leptonic photon Z l are reconsidered via the e + e - -> mu + mu - process at the Compact Linear Collider (CLIC) with the updated center-of-mass energies (380, 1500, and 3000 GeV). We show that new generation colliders as CLIC can observe the massive leptophilic vector boson Z l with mass up to the center-ofmass energy, provided that the leptonic coupling constant is g l >= 10 - 3 . In this study, we also estimated the cross sections by artificial neural networks using the theoretical results we obtained for CLIC. According to the results obtained, it was seen that these predictions could be made through machine learning.SCOAP3Funded by SCOAP3 under Creative Commons License, CC-BY 4.0

NAZIM BİÇİMİ AÇISINDAN HACI TAŞAN’IN ESERLERİNİN İNCELENMESİ

Yöresel Türk müziğinin önemli kaynak kişilerinden Hacı Taşan’ın icra ettiği 13 adet eserin edebî açıdan incelenmesinin amaçlandığı bu çalışmada eserler, sözlerin yapısı ve nazım biçimi ekseninde incelenmiştir. İncelenen eserlerin büyük çoğunluğunda 11’li hece ölçüsünün kullanıldığı, 2 eserde 7’li ve bir eserin bazı dizelerinde ise 8’li hece ölçüsüne yer verildiği tespit edilmiştir. İncelenen 13 adet eserin 8 tanesinin “türkü”, 3 tanesinin “koşma” ve 2 tanesinin “mâni” nazım biçiminde olduğu tespit edilmiştir. Eserlerin tamamında aşk, ayrılık, kavuşma, ölüm olmak üzere birbiriyle de ilişki içerisindeki dört konu işlenmiştir. Hacı Taşan’ın incelenen eserlerinde kullandığı bazı sözcüklerin yapılan diğer çalışmalarda farklı yazıldığı tespit edilmiştir. Eserlerin hangi yöreye ait olduğunun şüpheli olduğu durumlar için kaynak kişi icrasındaki söz unsurlarının incelenmesinin çözüm üretebileceği sonucuna ulaşılmıştır. Bu çalışmada incelenen eserlerin sözcüklerindeki farklılıklar ve eser isimlerinin metinle uyumsuz olması gibi bulgulara ulaşıldığı için derleme çalışmaları ile kayıt altına alınan yöresel Türk müziği eserlerinin söz unsurlarının yeniden ele alınması önerilmektedir

The use of special teaching methods by violin instructors in the early stages of education for young students

Eğitim Bilimleri Enstitüsü, Güzel Sanatlar Eğitimi Ana Bilim Dalı, Müzik Eğitimi Bilim DalıBu araştırma, erken yaş keman eğitiminde kullanılan özel öğretim yöntemlerinin belirlenmesini amaçlamaktadır. Erken yaş, öğrenmenin ve yeteneklerin hızlı geliştiği, müzikal duyarlılığın arttığı bir dönem olarak kabul edilmektedir. Bu bağlamda çalgı eğitiminde kullanılan yöntemlerin çocuğun müzikal yaşantısında olumlu etkiler sağlayacağı düşünülmektedir. Araştırma taşıdığı amaç doğrultusunda nitel bir çalışmadır. Araştırmanın çalışma grubunu Mersin Üniversitesi Devlet Konservatuvarı'nda erken yaş keman eğitimi veren 5 öğretim elemanı oluşturmuştur. Çalışma grubuna araştırmacı tarafından hazırlanan ve uzman görüşü alınan yarı yapılandırılmış görüşme formu uygulanmış, alt problemler doğrultusunda analiz edilmiştir. Elde edilen bulgular sonucunda, erken yaş keman eğitimi veren öğretim elemanlarının keman eğitimi sürecinde özel öğretim yöntem ve yaklaşımlarından Dalcroze, Orff, Kodaly ve Suzuki Yetenek Eğitimini kullandıkları sonucuna ulaşılmıştır.This research aims to determine the special teaching methods used in early age violin education. Early age is considered a period in which learning and skills develop rapidly and musical sensitivity increases. In this context, it is believed that the methods used in instrumental education will have positive effects on the child's musical experience. The research is a qualitative study in line with its purpose. The research group consists of 5 violin teachers who provide early age violin education at Mersin University State Conservatory. A semi-structured interview form prepared by the researcher and validated by experts was applied to the study group and analyzed according to sub-problems. As a result of the findings, it was concluded that violin teachers providing early age violin education use special teaching methods and approaches such as Dalcroze, Orff, Kodaly, and Suzuki Talent Education

Improvement in performance of SnSe-based photodetectors via post deposition sulfur diffusion

The work represents an enhancement in the photodetector properties of thermally evaporated SnSe thin films through both annealing and sulfurization processes. X-ray diffraction analysis showed the formation of SnSe 1-x S x alloy with a graded composition that was more S -rich near the surface when the sulfurization process was applied at 350 degrees C. Scanning electron microscopy results indicated that increasing the annealing temperature from 300 degrees C to 350 degrees C changed the microstructure greatly. When the sulfurization temperature was increased from 300 degrees C to 350 degrees C, the direct band gap of SnSe thin films decreased from 1.38 eV to 1.30 eV while the indirect band gap reduced from 0.91 eV to 0.71 eV. Raman spectra also confirmed the development of phase of SnSe 1-x S x for the sulfurized sample at 350 degrees C. Photocurrent-time curves of devices fabricated on all films demonstrated that sulfurization at high temperature increased the photocurrent values. It was further determined that devices made on sulfurized layers had smaller rise/fall times of 2.57/2.33 s compared to those fabricated on non-sulfurized films. The best responsivity and detectivity values were achieved as 2.07 x 10 -1 A/W and 1.19 x 10 7 Jones, respectively, for photodetectors fabricated on layers sulfurized at 350 degrees C

Lepiota castanea mushroom growing in Turkiye does not contain phallotoxins and amatoxins

The number of poisoning cases caused by the Lepiota genus is globally increasing. This genus has more poisonous species than the Amanita genus, and many Lepiota species can cause severe toxicity and death if ingested. As recognized in the literature, L. castanea is a toxic species containing amatoxin. Although crude analytical methods have shown that L. castanea contains amatoxins, more recent and sensitive analyses suggest otherwise. Toxin concentrations can vary even among the same fungal species due to geographical and climatic differences. Therefore, this confusion can be resolved by analyzing L. castanea toxins from different geographical regions. This study aimed to demonstrate the toxin levels of L. castanea collected from forests in different regions of Turkiye (Istanbul and Kocaeli) using sensitive methods. The collected mushrooms were analyzed for alpha amanitin, beta amanitin, gamma amanitin, amanin, phallacidin, and phalloidin levels using RP-HPLC-UV and LCESI-MS/MS methods. L. castanea mushroom was found to be free of amatoxin and phallotoxin. Our study revealed for the first time that L. castanea mushrooms from different geographical regions of Turkiye do not contain amatoxin and phallotoxin. Supporting these findings with new studies from different parts of the world would be appropriate.Ankara University Research Fund Proj- ect [15H0430001]This project is supported by Ankara University Research Fund Proj- ect Number: 15H0430001. The icons used in the graphical abstract were taken from www.flaticon.com , which can be subscribed to free of charge

Fabrication and device characterization of p-ZnTe/n-Si nanodiodes

Fen Bilimleri Enstitüsü, Fizik Ana Bilim DalıBu tezde ZnTe/Si p-n heteroeklem yapısından oluşan nanodiyotların üretimi ve aygıt karakteristiklerinin incelenmesi amaçlanmıştır. MACE yöntemi ile önceden temizlenmiş (110) yönelimli n-tipi tek kristal Si dilimlerinin yüzeyinde dikey olarak sıralanmış ortalama 1 µm uzunluklu Si nanoteller sentezlendi. Daha sonra, ~ 750 nm kalınlığında ZnTe ince filmi Si nanotel kümeleri üzerine RF magnetron saçtırma yoluyla direkt olarak depolandı. Elektriksel ölçümler, üretilen aygıtın karanlıkta ve oda sıcaklığında yüksek doğrultma oranına (~ 10^4), düşük idealite faktörüne (n = 2,3), düşük ters sızıntı akımına (~ 10^-7) ve düşük seri dirence (Rs = 0,93 k?) sahip olduklarını ortaya koydu. AM 1.5G aydınlatma şartları altında 300 mV'luk açık devre gerilimi ölçüldü ve 1 saniyeden daha küçük zamanda ışığa karşı tepki gözlendi. Spektral ışık duyarlılığı ölçümleri, nanodiyotların özellikle elektromanyetik spektrumun NIR bölgesindeki fotonlara oldukça iyi tepki verdiğini gösterdi. ZnTe ince filmi ve dikey olarak dizilmiş Si nanotel kümelerinin bir araya gelmesiyle oluşan heteroeklem nanodiyotların gözlenen performansı, üretilen aygıtların özellikle NIR fotodetektörler olmak üzere gelecekteki optoelektronik cihaz uygulamaları için umut verici olduğunu ortaya koymaktadır.In this thesis, it is aimed to fabricate nanodiodes consisting of ZnTe/Si p-n heterojunction structure and examine their device characteristics. Using the MACE method, vertically aligned Si nanowires with an average length of 1 µm were synthesized on the surface of pre-cleaned (110) oriented n-type single crystal Si wafers. Then, ~ 750 nm thick ZnTe thin film was directly deposited onto Si nanowire arrays via RF magnetron sputtering. Electrical measurements show that the fabricated device has high rectification ratio (~ 10^4), low ideality factor (n = 2.3), low reverse leakage current (~ 10^-7) and low series resistance (Rs = 0.93 k?) in the dark and at room temperature. Under AM 1.5G illumination conditions, an open circuit voltage of 300 mV was measured and the response to light was observed in less than 1 second. Photoresponsivity measurements showed that the device responded quite well to photons, especially in the NIR region of the electromagnetic spectrum. The observed performance of heterojunction nanodiodes formed by combining ZnTe thin film and vertically aligned Si nanowire arrays reveals that the fabricated devices are promising for future optoelectronic device applications, especially NIR photodetectors