CARAMANIAN ORTHODOX TURKS WHO IMMIGRATED TO GREECE FROM MUSTAFAPASHA BECAUSE OF THE POPULATION EXCHANGE

Caramanians, who were Turkish-speaking Orthodox Christians and used Greekalphabet in their writings, lived especially in Anatolia (Karaman, Konya, Kayseri,Isparta, Nevsehir, Nigde, Aksaray, Burdur, Aydin and Karadeniz etc.), İstanbul,Syria and Balkan area. The Caramanian Orthodox Turks lived generally in the Cappadocia Region. Caramanian Orthodox Turks, who had lived in Cappadocia(Nevsehir, Urgup, Sinasos), Derinkuyu (Suvermez, Yazıhoyuk, Zile), Niğde (Golcuk,Misti/Misli Fertek, Sementra, Andaval, Haskoy, Aravan/Kumluca,Kurdanos/Hamamli, Bor), Aksaray (Guzelyurt, Uluagac), Kayseri (Incesu,Zincidere, Pinarbasi, Endurluk, Develi) were subjected to the forced emigration to Greece as of May 1st, 1923 in accordance with the "Convention and Protocol relating to Exchange of Greek and Turkish People" signed on January 30th, 1923 between the Grand National Assembly of Turkey and the Greek Parliament. Today,Caramanian Orthodox Turks living in such settlements like Thessaloniki, Larissa,Eviya Island (Prokopi, Neasinasos, Neapoli, Neagelveri, Cappadocia) Athens, Preaand Halkida have rich oral and written cultural products. Mustaphapasha (Sinasos)town is one of the centers of science, art, commerce and religion of Caramanian Orthodox Turks in the Cappadocia Region. Caramanian Ortodox Turks living in this town have been settled in different regions of Greece as a result of the population exchange. This paper deals with the current social life, ways of protecting their cultures, associations and foundations, customs and traditions, folksongs, poems, lullabies, threnodies etc. by providing information about the history and anthropology of Caramanian Orthodox Turks emigrating to Greece from Mustafa pasha

Laboratory and telescope use of the NICMOS2 128 x 128 HgCdTe array

The second generation of Hubble Space Telescope (HST) instruments will include a near-infrared instrument. This choice has driven the development of near-infrared arrays to larger sizes and lower read noises. Rockwell International has delivered an array for use in the Near Infrared Camera and Multi-Object Spectrometer (NICMOS) instrument; this array has been dubbed NICMOS2. NICMOS2 is a 128x128 array of HgCdTe diodes In-bonded to a switched MOSFET readout. The readout was specifically designed for astronomical use with the HST requirement of low read noise a prime goal. These arrays use detector material which is similar to that used by Rockwell in previous arrays (e.g., HgCdTe produced on a sapphire substrate), but the NICMOS2 devices differ substantially from other 128x128 arrays produced by Rockwell in having a read noise of only 30 electrons when read out using appropriate correlated sampling. NICMOS2 has now been characterized in the laboratory, and it has been used on groundbased telescopes

Defendroid: real-time Android code vulnerability detection via blockchain federated neural network with XAI

Ensuring strict adherence to security during the phases of Android app development is essential, primarily due to the prevalent issue of apps being released without adequate security measures in place. While a few automated tools are employed to reduce potential vulnerabilities during development, their effectiveness in detecting vulnerabilities may fall short. To address this, “Defendroid”, a blockchain-based federated neural network enhanced with Explainable Artificial Intelligence (XAI) is introduced in this work. Trained on the LVDAndro dataset, the vanilla neural network model achieves a 96% accuracy and 0.96 F1-Score in binary classification for vulnerability detection. Additionally, in multi-class classification, the model accurately identifies Common Weakness Enumeration (CWE) categories with a 93% accuracy and 0.91 F1-Score. In a move to foster collaboration and model improvement, the model has been deployed within a blockchain-based federated environment. This environment enables community-driven collaborative training and enhancements in partnership with other clients. The extended model demonstrates improved accuracy of 96% and F1-Score of 0.96 in both binary and multi-class classifications. The use of XAI plays a pivotal role in presenting vulnerability detection results to developers, offering prediction probabilities for each word within the code. This model has been integrated into an Application Programming Interface (API) as the backend and further incorporated into Android Studio as a plugin, facilitating real-time vulnerability detection. Notably, Defendroid exhibits high efficiency, delivering prediction probabilities for a single code line in an average processing time of a mere 300 ms. The weight-sharing transparency in the blockchain-driven federated model enhances trust and traceability, fostering community engagement while preserving source code privacy and contributing to accuracy improvement

Android source code vulnerability detection: a systematic literature review

The use of mobile devices is rising daily in this technological era. A continuous and increasing number of mobile applications are constantly offered on mobile marketplaces to fulfil the needs of smartphone users. Many Android applications do not address the security aspects appropriately. This is often due to a lack of automated mechanisms to identify, test, and fix source code vulnerabilities at the early stages of design and development. Therefore, the need to fix such issues at the initial stages rather than providing updates and patches to the published applications is widely recognized. Researchers have proposed several methods to improve the security of applications by detecting source code vulnerabilities and malicious codes. This Systematic Literature Review (SLR) focuses on Android application analysis and source code vulnerability detection methods and tools by critically evaluating 118 carefully selected technical studies published between 2016 and 2022. It highlights the advantages, disadvantages, applicability of the proposed techniques and potential improvements of those studies. Both Machine Learning (ML) based methods and conventional methods related to vulnerability detection are discussed while focusing more on ML-based methods since many recent studies conducted experiments with ML. Therefore, this paper aims to enable researchers to acquire in-depth knowledge in secure mobile application development while minimizing the vulnerabilities by applying ML methods. Furthermore, researchers can use the discussions and findings of this SLR to identify potential future research and development directions

The Immunological Effectiveness of Some Common Plants

Three plant species were picked randomly and their alcoholic extracts have been screened to know their effects on the phagocytic capability and intracellular killing of yeast by human peripheral macrophages. Macrophage cultures were incubated with different concentration of each plant extract: for 15 min., 30 min .and 45 min. The phagocytes activity in Iresine herbstii extract was significantly (p?0.05) increased with increasing dose and time of incubation. In Mentha piperita extract, increasing in dose and time of incubation leads to elevate phagocytic capbility, especially in the dose of 20% and 25% of plant extract, perhaps because the antimicrobial and antiviral activities of this plant, as well as strong antioxidant and antitumor actions. While in Elettaria cardamomum, a significant elevation has been observed in phagocytic efficiency when the dose of extract increase to 15%, then decreased in the subsequent doses (20% and 25%), in three periods of time. These findings may suggest that cardamom exert immunomodulatory roles

Prediction of a deletion copy number variant by a dense SNP panel

<p>Abstract</p> <p>Background</p> <p>A newly recognized type of genetic variation, Copy Number Variation (CNV), is detected in mammalian genomes, e.g. the cattle genome. This form of variation can potentially cause phenotypic variation. Our objective was to determine whether dense SNP (single nucleotide polymorphisms) panels can capture the genetic variation due to a simple bi-allelic CNV, with the prospect of including the effect of such structural variations into genomic predictions.</p> <p>Methods</p> <p>A deletion type CNV on bovine chromosome 6 was predicted from its neighboring SNP with a multiple regression model. Our dataset consisted of CNV genotypes of 1,682 cows, along with 100 surrounding SNP genotypes. A prediction model was fitted considering 10 to 100 surrounding SNP and the accuracy obtained directly from the model was confirmed by cross-validation.</p> <p>Results and conclusions</p> <p>The accuracy of prediction increased with an increasing number of SNP in the model and the predicted accuracies were similar to those obtained by cross-validation. A substantial increase in accuracy was observed when the number of SNP increased from 10 to 50 but thereafter the increase was smaller, reaching the highest accuracy (0.94) with 100 surrounding SNP. Thus, we conclude that the genotype of a deletion type CNV and its putative QTL effect can be predicted with a maximum accuracy of 0.94 from surrounding SNP. This high prediction accuracy suggests that genetic variation due to simple deletion CNV is well captured by dense SNP panels. Since genomic selection relies on the availability of a dense marker panel with markers in close linkage disequilibrium to the QTL in order to predict their genetic values, we also discuss opportunities for genomic selection to predict the effects of CNV by dense SNP panels, when CNV cause variation in quantitative traits.</p

Karakteristik dan Perilaku Merpati Tinggi Lokal Jantan dan Betina

This study aims to 1) describe the qualitative characteristics of high pigeon (the coat color, head shape, tail shape, body shape, eye shape, the shape of the wings, beak shape and the shape of the foot at the local high pigeon male and female); 2) describe the behavior of pigeons move higher (fly, hanging, running, fighting), and mating behavior (male approaches the female, browse, and making out). This research are conducted in August 2015 in the Rawa subur Road No. 49, Enggal Centre Tanjung Karang, Bandar Lampung. This study used a descriptive exploratory conduct direct observation of the behavior of pigeons and doves characteristics of male and female local high. The results showed qualitative characteristics pigeons local high male and female varied: head shape (type round, type jenong, and type turtledove), beak shape (type rambon and type taper), shape (type of banana bod and ball type), the type of hair (tenuous and short) and the frequency and timing of moving the highest relative to the local high pigeon is flying, while the mating behavior is investigate

Focusing on antimicrobial resistant infections –are we missing the forest for the trees and the patients for pathogens?

Antimicrobial resistance (AMR) is a challenge because it is associated with worse patient outcomes. To solve the problem will take development of interventions and policies which improve patient outcomes by prolonging survival, improving patient symptoms, function and quality of life. Logically, we should look to focusing resources in areas that would have the greatest impact on public health. AMR takes the approach of focusing on individual pathogens and “pathogen-focused” development. However, evaluating overall infections and their impact on patient outcomes reveals that 17 of 18 infection deaths are associated with susceptible pathogens. Here we discuss recentering on patients and patient outcomes instead of pathogens, and propose six suggestions on how a patient focus impacts areas and incentives for clinical research