Digital Legal Information: Ensuring Access to the Official Word of the Law

In the United States today, digital versions of current decisions, bills, statutes, and regulations issued by federal and state entities are widely available on publicly accessible Internet Web sites. Worldwide, official legal information issued by international organizations and foreign governments is also becoming available on the Web. However, there are currently no standards for the production and authentication of digital documents. Moreover, the information is sometimes available only for a short time and then disappears from the site. Most of that digital information provides only a right of access, and no ownership, or control over the data, unless it is downloaded on a server, or stored on a CD. The long-term access to digital legal information is a matter of concern

Doğu Anadolu Bölgesi’nde Organik Kuru Fasulye Üretiminin Araştırılması

Bu çalışmanın amacı, ahır gübresi, mikrobiyal gübre (BA–142, M–3 bakterileri) ve ticari gübre uygulamalarının arpa bitkisi ile münavebeli yetişiciliği yapılan fasulye bitkisinin verim ve toprak makro element içeriği (NPK) üzerine etkilerini belirlemektir. İlk ekim yılını takiben en yüksek fasulye verimi mineral gübre uygulanmasından elde edilmiş daha sonraki yıllar ise fasulyeden en yüksek verim sırasıyla çiftlik gübresi, ticari gübre, M-3, BA-142 ve hiç gübre kullanılmayan kontrol grubundan elde edilmiştir. Yapılan toprak analizlerinde ise yıllar itibariyle deneme parsellerindeki toprakların azot, fosfor ve potasyum değişimleri incelenmiş ve fasulye verimi ile olan ilişkisi değerlendirilmiştir

Study of delay prediction in the US airport network

In modern business, Artificial Intelligence (AI) and Machine Learning (ML) have affected strategy and decision-making positively in the form of predictive modeling. This study aims to use ML and AI to predict arrival flight delays in the United States airport network. Flight delays carry severe social, environmental, and economic impacts with them, and deploying ML models during the process of strategic decision-making, can help to reduce the impacts of these delays. To achieve the result of the study, a literature study and critical appraisal have been carried out on previous studies and research relating to flight delay prediction. In the literature study, the datasets used, selected features, selected algorithms, and evaluation tools used in previous studies have been analyzed. The results from the literature study and critical appraisal have influenced the decisions made in the methodology for this study. In the methodology, a choice is made for two public datasets, one of the domestic flight data of 2017 and one of the weather data of 2017. These two datasets are then processed in a custom-designed data pipeline which is built using Spark. The processed data is split into training data, validation data, and testing data. The training data and validation data are used to train and hyperparameter tune several ML models using both Spark and H2O. Subsequently, these ML models are evaluated and compared based on performance metrics obtained using the testing data. From this comparison, the best-performing model is presented as a suitable solution for arrival flight delay prediction. The predictive model with the best performance among logistic regression, random forest, gradient boosting machine, and feed-forward neural networks ended up being the gradient boosting machine with far better predictive modeling performance. This solution can be deployed as a supportive ML model during strategic decision-making

The Tendency of Turkish Pre-service Teachers’ to Pose Word Problems

The aim of this study was to identify the problem posing tendency of preservice teachers (primary and mathematics) in structured problem posing situations. Participants were selected using a two-step sampling process in order to prevent bias. In the first sampling process, a total of 109 pre-service teachers participated in the study. Of these participants, 48 were pre-service primary school mathematics teachers and 61 were pre-service primary teachers who were in their sixth term of school. In the second sampling process, 10 volunteer participants were selected using purposeful sampling. It was found that participants had a tendency to pose result-centered problems (contextually inappropriate and irrelevant result-focused problems) and context-centered problems (standard and non-standard word problems). In some cases, participants did not pose any word problems

DETERMINING THE COGNITIVE STRUCTURES AND MISCONCEPTIONS ABOUT CHROMOSOME AND HOMOLOGOUS CHROMOSOME CONCEPTS IN HIGH SCHOOL STUDENTS: DRAWING-WRITING TECHNIQUE

This study aims to determine the cognitive structures related to the chromosome and homologous chromosomes as well as the misconceptions of 10th-grade high school students. 140 10th-grade high school students participated in the study. Data were collected using the drawing-writing technique. The students were asked to draw the chromosome and homologous chromosomes separately, to identify their elements, and to write an explanatory sentence about these concepts. The drawings and explanations were analyzed separately and the students’ cognitive structures and misconceptions were investigated. The analyses revealed students have misconceptions about the chromosome and homologous chromosomes. The study results emphasize that effectively teaching the concept of chromosome and homologous chromosomes; the basic concept of the cell cycle, is fundamental for further science studies.  Article visualizations

PANI Konsantrasyonunun PP/PANI Kompozitlerinin Mekanik Özelliklerine Etkisi

Bu çalışmada, farklı konsantrasyonlarda (ağırlıkça %0,3-%3,0 arası) Polyanilin (PANI) katkısının Polipropilen/Polyanilin (PP/PANI) film kompozitlerinin mekanik özelliklerine etkisi araştırılmıştır. Sıcak presleme tekniği ile elde edilen kompozit filmlerin, yüzey özellikleri ve yapısal morfolojileri (SEM ve FTIR), termal özellikleri (TG) belirlenmek üzere karakterize edilmiştir. PANI katkısının polipropilen filmlerin mekanik özelliklerine etkisi çekme testleri ile incelenmiştir. Özellikle, kompozitlerin çekme dayanımı, Elastisite modülü ve yüzde kopma uzama miktarları test edilmiştir. Sonuçlarımıza göre, PANI katkısının polipropilenin mekanik özelliklerinde belirgin bir etkisi olduğu görülmüştür. Çekme gerilimi, PP/0.6 wt.% PANI kompozitlerinde en yüksek değere ulaşılmıştır.In this study, the effect of PANI additive with different concentrations (0.3-3.0 wt.%) on mechanical properties of Polypropylene/Polyaniline (PP/PANI) film composites have been investigated. The composites films obtained from the hot pressing technique have been characterized to determine their surface properties and structural morphology (SEM and FT-IR), thermal properties (TG). The effects of PANI additive on mechanical properties of polypropylene have been examined by tensile tests. In particular, tensile strength, Young's modulus and percentage strain at break of the composites have been tested. According to our results, it has been observed that the PANI additive in polypropylene had a significant impact on its mechanical properties. The tensile strength has been reached highest value in PP/0.6 wt.% PANI composites

Klasifikacija vrsta drva prema slikama uz pomoć dvodimenzionalne konvolucijske neuronske mreže

The woodworking industry’s recognition and classification of timber is essential for trade, production and timber science. Traditional methods of identifying wood types are complex, time-consuming, costly and require expertise in wood science. Traditional techniques have been replaced by convolutional neural networks (CNNs), a deep learning tool to better identify wood species. In contrast to earlier studies that used pretrained models, a novel architecture designed explicitly for the WOOD-AUTH dataset was proposed in this study to develop a new 2D CNN model. The data collection encompasses high-level visual representations of 12 distinct types of timber. It is aimed to create a simpler and faster model as an alternative to time-consuming and heavy wood classification models. Compared to previous studies, this research worked with a newly structured 2D CNN network based on 12 wood species. High accuracy and fast computation time were achieved using fewer numbers (three layers) of the convolutional neural network. The proposed model achieved 94 % accuracy, 87 % precision, 81 % recall, 80 % F1 score and 112 minutes 27 seconds computation time. The 2D CNN model performed better than the transfer learning models regarding training epochs. The primary benefit of the model is its ability to achieve high accuracy with lower computation time, even at high epochs compared to other models. The introduced 2D CNN model produced satisfactory outcomes for wood species classification.Identifikacija i klasifikacija drva u drvnoj industriji ključna je za trgovinu, proizvodnju i znanost o drvu. Tradicionalne metode identifikacije vrste drva složene su, dugotrajne i skupe te zahtijevaju stručnost s područja znanosti o drvu. Za bolju identifikaciju vrste drva tradicionalne su metode zamijenjene konvolucijskim neuronskim mrežama (CNN), odnosno alatom za duboko učenje. Za razliku od ranijih studija koje su se koristile unaprijed obučenim modelima, u ovoj je studiji predložena nova arhitektura dizajnirana upravo za skup podataka WOOD-AUTH kako bi se razvio novi 2D CNN model. Zbirka podataka obuhvaća vizualne prikaze visoke razlučivosti 12 različitih vrsta drva. Cilj je bio stvoriti jednostavniji i brži model kao alternativu dugotrajnim i složenim modelima klasifikacije drva. Za razliku od prethodnih istraživanja, u ovom je istraživanju primijenjena nova 2D CNN mreža koja se temelji na 12 vrsta drva. Visoka točnost i brzo vrijeme izračuna postignuti su korištenjem manjeg broja slojeva (tri sloja) konvolucijske neuronske mreže. Predloženim je modelom postignuta točnost od 94 %, preciznost od 87 %, opoziv od 81 %, F1 rezultat od 80 % i vrijeme izračuna od 112 minuta i 27 sekundi. Model 2D CNN pokazao se boljim od modela transfernog učenja u smislu epohe poduke. Primarna prednost modela jest njegova sposobnost postizanja visoke točnosti uz kraće vrijeme izračuna, čak i pri visokim epohama u usporedbi s drugim modelima. Prezentirani 2D CNN model dao je zadovoljavajuće rezultate za klasifikaciju vrste drva

Is tenofovir disoproxil nephrotoxic in all patients? side effects of tenofovir and entecavir on kidney

Background: Hepatit B virus (HBV) is one of the main causes of liver related morbidity and mortality in worldwide. This condition is also a significant healthcare problem in Turkey. Entecavir (ETV) and tenofovir (TDF) are potent nucleos(t)ide analogues (NAs) recommended for the treatment of chronic HBV (CHB) infection. The aim of the study was to determine the association of NAs and nephrotoxicity in our CHB cohort.Methods: Between the January 2011-February 2021, there were 294 patients treated with TDF (N=194) and ETV (N=100). Glomerular filtration rate (GFR) was calculated by the modification of diet in renal disease (MDRD) method. Kidney function tests were assessed at baseline and follow-up visits.Results: There were 294 patients in the total group. The mean follow-up period was 66±18 months. Age and sex distributions and baseline assessments including liver function tests, creatinine, GFR, HBV DNA values and pathology scores (HAI and fibrosis) were similar between TDF (N=194) and ETV (N=100) groups. Creatinin and GFR assessed at the last visit were 0.81±0.01 g/dl and 102.94±19.78 ml/min for TDF and 0.81±0.013 g/dl and 104.65±19.05 ml/min for ETV. These values were not significant between the both treatment groups. In terms of nephrotoxicity, none of the patients had significant changes in terms of creatinine and GFR that may require dose adjustment.Conclusions: We showed that the use of both drugs led to a decrease in GFR that was not clinically important in chronic hepatitis B patients with normal baseline renal tests and without co-morbidity

Isolation of Acanthamoeba isolates belonging to T2, T3, T4 and T7 genotypes from environmental samples in Ankara, Turkey

Acanthamoeba keratitis is a blinding infection that is becoming increasingly important in human health. Early diagnosis is a prerequisite for successful treatment and requires identification of Acanthamoeba at the genotypic level. The genus Acanthamoeba consists of both pathogenic and non-pathogenic species and has been recently classified into 13 different genotypes, T1-T12 and T14. More importantly, 95% of Acanthamoeba isolates that produce keratitis belong to T4 genotypes. In this study, we attempted to determine whether predominance of T4 isolates in Acanthamoeba keratitis is due to greater virulence or greater prevalence. We isolated 18 Acanthamoeba isolates from environmental samples in Ankara, Turkey and determined their pathogenic potential by means osmotolerance, temperature tolerance and in vitro cytotoxicity assays using corneal epithelial cells. Ribosomal DNA sequencing revealed that 10 isolates belong to T2, 5 belong to T3, 2 belong to T4 and one belongs to T7 genotype. As expected, T3 and T4 isolates exhibited the most pathogenic traits and were osmotolerant, temperature tolerant and exhibited severe corneal epithelial cell cytotoxicity indicating their pathogenic potential. Overall these data indicate that high frequency of T4 isolates in keratitis cases may well be due to their greater virulence. This is the first report presenting environmental distribution of Acanthamoeba in Ankara, Turkey