Análisis comparativo del impacto, de la segregación de los datos por género, en los protocolos de investigación de fisiología reproductiva y cardio-respiratoria

Es un hecho conocido que el dimorfismo sexual se presenta en la mayoría de las especies animales. Las diferencias que esto conlleva, tienen una base genética que sustenta características físicas propias de machos o hembras. Conocido esto, es evidente la necesidad de determinar la incidencia genérica en el funcionamiento de cualquier organismo. Sin embargo, el presente análisis, ha permitido comprobar que, la inclusión en la segregación de los resultados por género en estudios de Bio-Medicina (clínicos y pre-clínicos) aún no es algo generalizado. Para ello, se han revisado y combinado los resultados de un conjunto de estudios (fechados entre 2011 y 2017) escogiéndose dos áreas (en cuyas fisio-patologías se acepte diferente grado de impacto del género): aparato reproductivo y el sistema cardio-respiratorio. Los resultados obtenidos confirman la necesidad de concienciar a la comunidad científica de la importancia de la inclusión de la variable “género” en este tipo de estudios.It is a known fact that sexual dimorphism occurs in most animal species. The differences that this entails have a genetic basis that supports physical characteristics of males or females. Once this is known, the need to determine the generic incidence in the functioning of any organism is evident. However, the present analysis has shown that inclusion in the segregation of results by gender in Bio-Medicine studies (clinical and pre-clinical) is not yet widespread. For that, the results of a series of studies (dated between 2011 and 2017) have been reviewed and combined, choosing two areas (in whose physio-pathologies a different degree of gender impact is accepted): reproductive system and the cardio-respiratory system. The results obtained confirm the need to make the scientific community aware of the importance of including the gender variable in this type of studies

Social Role Valorization Theory in Social Service Applications Implementations: The case of Deafs and Blinds in the Ottoman Empire

Sosyal Rol Valörizasyon (SRV) Kuramı çeşitli sosyal kategorilere yerleştirilen bireylerin farklılıkları sebebiyle sosyal değersizleştirilme ve değersiz rollerle ilişkilendirilme süreçlerini açıklamaya yönelen bir yaklaşımdır. SRV Kuramı değersizleştirilmiş bir kategori olarak engellilerin, içinde yaşadıkları toplumca muteber sayılan sosyal roller ifa edebilme kapasitelerinin geliştirilmesi yoluyla toplumsal konumlanışlarının olumlu yönde değişeceğini önermektedir. Çalışmada SRV yaklaşımının önermeleri ile engellilik olgusunun Türk toplumundaki anlamlandırılma formları arasında ilişki bulunduğunu; SRV kuramının bir sosyal hizmet uygulama yaklaşımı olarak kullanılmasının ihtiyaç duyduğu sosyokültürel zeminin Türk toplumunda mevcut bulunduğunu ve özellikle Osmanlı döneminde işitme engellilerin devlet kurumlarında istihdamları, görme engellilerin din hizmetleri ve hafızlık müessesesinde istihdamları gibi örneklerle ortaya koyma amacındadır.Social Rol Valorization (SRV) theory is an approach intending to explicate the processes which socially devaluate those individuals located in various social kategories, and designate them with devalued roles due to their differences. SRV Theory proposes that social positions of disabled persons, as being devalued category, can glow up by improving their capacity to undertake such social roles valued by the society they live in. This study aims to demonstrate that there is a remarkable relevance between forms of interpretation of disability in Turkish society and the main propositions of SRV Theory; Turkish society holds the proper socio-cultural background required SRV theory to be utilized as a socialwork implementation approach. These views have been discussed by holding up the employment of deaf individuals in state agencies and employment of blind individuals in religious services and Quran memorization sector in Ottoman period as examples

SARS-CoV-2’ye Karşı Doğal Terapötiklerin Potansiyeli: Fenolik Bileşikler ve Terpenler

2019 yılının sonlarında Çin’de ortaya çıkan şiddetli, koronavirüs akut solunum yolu sendromu-koronavirüs-2’nin (SARS-CoV-2) neden olduğu koronavirüs hastalığı-2019, insan yaşamının hemen hemen her sektörünü etkileyen ve dünya ekonomisine büyük zarar veren benzeri görülmemiş bir küresel sağlık krizi meydana getirmiştir. SARS-CoV-2, yalnızca üst solunum yolu enfeksiyonuna neden olmakla kalmayıp aynı zamanda alt solunum yolu mukozası tutulumu da yapabilen ve bu sebeple pnömoniye neden olarak bazı hastalarda ölüme yol açan viral bir solunum yolu virüsüdür. Şu anda SARS-CoV-2 tedavisi için kanıtlanmış bir ilaç olmaması ile birlikte, tedavi için birçok kimyasal ve doğal aktif bileşik araştırmacılar tarafından test edilmiştir. Bu bitkisel bazlı antiviraller, daha az toksik oldukları ve enfeksiyöz mikroorganizmalar tarafından direnç geliştirilmesi daha düşük olasılıklı olduğu için birçok araştırmanın konusu olmuştur. Doğal terapötiklerin viral replikasyonu engellediği de birçok çalışmada bildirilmiştir. Bu derlemede, antiviral aktiviteye sahip olduğu bilinen doğal terapötikler olan fenolik bileşikler ve terpenler, SARS-CoV-2 tedavisinde kullanım potansiyelleri açısından ele alınmıştır

A research determines the interaction among employee's prosocial organizational behaviors in hotel establishments

Bu araştırma, konaklama işletmelerinde işgörenlerin prososyal örgütsel davranışları arasındaki etkileşimin incelenmesi amacını taşımaktadır. Konaklama işletmelerinde hizmet süreçleri, işgören-işgören ve işgören-müşteri etkileşimine dayalıdır. Bu sebeple, konaklama işletmelerinde işgörenlerin prososyal örgütsel davranışları, işgören-müşteri; işgören-işgören etkileşimi çerçevesinde ele alınmıştır. Büyük bir konaklama işletmesinin ön hat çalışanlarının oluşturduğu örneklemden, anket yöntemiyle elde edilen veriler; faktör analizi, korelasyon analizi ve çoklu regresyon analizi yöntemleri vasıtasıyla değerlendirilmiştir. Araştırma bulgularına göre, araştırma kapsamındaki işletmede, işgörenlerin müşteri odaklı prososyal davranışları ile örgüt-işgören odaklı prososyal davranışları arasında anlamlı bir ilişki bulunduğu istatistiksel olarak kabul edilmiştir.This research investigates the interaction among employee’s prosocial organizational behaviors in hotel establishments. The service processes in hotel establishments based on among employee-employee and employee-customer interaction. Because of this reason, prosocial organizational behaviors of the employees in hotel establishments are examined within the framework of the interaction first between employee and customer and then between employee and employee. The data provided from a sample of the front line employees in a largescale hotel business are analyzed via factor analysis, correlation analysis and multiple regression analysis. According to the results, it is statistically supported that there is a relationship among employee’s customer – oriented and employee/organization – oriented prosocial service behaviors

Particle swarm based arc detection on time series in pantograph-catenary system

Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained.Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained

A Deep Learning Model for Automated Segmentation of Fluorescence Cell images

Deep learning techniques bring together key advantages in biomedical image segmentation. They speed up the process, increase the reproducibility, and reduce the workload in segmentation and classification. Deep learning techniques can be used for analysing cell concentration, cell viability, as well as the size and form of each cell. In this study, we develop a deep learning model for automated segmentation of fluorescence cell images, and apply it to fluorescence images recorded with a home-built epi-fluorescence microscope. A deep neural network model based on U-Net architecture was built using a publicly available dataset of cell nuclei images [1]. A model accuracy of 97.3% was reached at the end of model training. Fluorescence cell images acquired with our home-built microscope were then segmented using the developed model. 141 of 151 cells in 5 images were successfully segmented, revealing a segmentation success rate of 93.4%. This deep learning model can be extended to the analysis of different cell types and cell viability

Influence of intermittent fasting during ramadan on circadian variation of symptom-onset and prehospital time delay in acute st-segment elevation myocardial infarction

WOS:000843327400001 PubMed ID:35975875Ramadan interferes with circadian rhythms mainly by disturbing the routine patterns of feeding and smoking. The objective of this study was to investigate the circadian pattern of ST elevation acute myocardial infarction (STEMI) during the month of Ramadan. We studied consecutive STEMI patients 1 month before and after Ramadan (non-Ramadan group-NRG) and during Ramadan (Ramadan group-RG). The RG group was also divided into two groups, based on whether they chose to fast: fasting (FG) and non-fasting group (NFG). The time of STEMI onset was compared. A total of 742 consecutive STEMI patients were classified into 4 groups by 6 h intervals according to time-of-day at symptom onset. No consistent circadian variation in the onset of STEMI was observed both between the RG (P = .938) and NRG (P = .766) or between the FG (P = .232) and NFG (P = .523). When analyzed for subgroups of the study sample, neither smoking nor diabetes showed circadian rhythm. There was a trend towards a delay from symptom onset to hospital presentation, particularly at evening hours in the RG compared with the control group. In conclusion, there was no significant difference in STEMI onset time, but the time from symptom onset to hospital admission was significantly delayed during Ramadan

Particle swarm based arc detection on time series in pantograph-catenary system

Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained.Pantograph-catenary system is the most important component for transmitting the electric energy to the train. If the faults have not detected in an early stage, energy can disrupt the energy and this leads to more serious faults. The arcs occurred in the contact point is the first step of a fault. When they are detected in an early stage, catastrophic faults and accidents can be avoided. In this study, a new approach has been proposed to detect arcs in pantograph-catenary system. The proposed method applies a threshold value to each video frame and the rate of sudden glares are converted to time series. The phase space of the obtained time series is constructed and the arc event is found by using particle swarm optimization. The proposed method is analyzed by using real pantograph-videos and good result have been obtained