By March 2020, a pandemic had been emerged Corona Virus Infection in 2019 (COVID-19), which was triggered through the sensitive pulmonary syndrome (SARS disease corona virus- 2 (SARS COV-2). Overall precise path physiology of SARS COV-2 still unknown, as does the involvement of every element of the acute or adaptable immunity systems. Additionally, evidence from additional corona virus groups, including SARS COV as well as the Middle East pulmonary disease, besides that, fresh discoveries might help researchers fully comprehend SARS CoV-2. Toll-like receptors (TLRs) serve a critical part in both detection of viral particles as well as the stimulation of the body's immune response. When TLR systems are activated, pro-inflammatory cytokines like interleukin 1 (IL1), IL6, or nuclear factors, in addition to helpful interferon, are secreted. TLRs such as TLR2, TLR3, TLR4, TLR6, TLR7, TLR8, or TLR9 might possibly have a role in COVID-19 infections. It's also important noting that while dealing with COVID-19 infections, researchers should consider both the good or detrimental impacts of TLR. TLRs might be a focus for reducing infections inside the initial phases of the illness or developing a SARS CoV-2 vaccine.
Background Commonly heard statements such as “Christmas comes around more quickly each year” suggest that the passage of time between annual events can become distorted, leading to the sensation of time passing more quickly than normal. At present however, it is unclear how prevalent such beliefs are and, what factors are predictive of it. Aim To explore the prevalence of beliefs that annual events such as Christmas (Study 1 UK sample) and Ramadan (Study 2 Iraqi sample) feel like they come around more quickly each year. To establish the association between distortions to the passage of time between annual events and emotional wellbeing, event specific enjoyment, memory function and self-reported attention to time. Methods Participants c
... Show MoreThis study was conducted during the period 1/9/2014 – 1/2/2015 and aimed to identify the polymorphisms of IGF-1 gene in broiler chickens and their effects on some biochemical traits. A total of 300 one-day-old broiler chicks (Cobb500, n=150; Hubbard F-15, n=150) were evaluated in this study. Blood samples were individually collected from all birds for DNA extraction. PCR-RFLP method being used for determination the genotypes of IGF-1 gene which then correlated with biochemical traits studied. Cobb500 broilers with TT genotype had significantly (p˂0.05) higher serum triglycerides values than those of TC and CC genotypes. Low density lipoprotein (LDL) were significantly (p˂0.05) higher in Hubbard F-15 broilers with TT genotype than those
... Show MoreA theoretical analysis studied was performed to study the opacity broadening of spectral lines emitted from aluminum plasma produced by Nd-YLF laser. The plasma density was in the range 1028-1026 )) m-3 with length of plasma about ?300) m) , the opacity was studied as function of plasma density & principle quantum number. The results show that the opacity broadening increases as plasma density increases & decreases with the spacing between energy levels of emission spectral line.
Detection of virulence gene agglutinin-like sequence (ALS) 1 by using molecular technology from clinical samples (
This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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تتناول هذه الورقة مخططات وسياسات الاستيطان في الضفة الغربية والقدس الشرقية منذ العام 1967، عبر سياسات قادها حزب العمل وأكملها حزب الليكود وكاديما وبقية الأحزاب الإسرائيلية، تلك السياسات التي استهدفت فرض السيطرة السياسية الكاملة على الأرض، وما نتج عن ذلك من سيطرة حصرية على الأرضوتقييد استخداماتها، ومحاصرة الوجود الفلسطيني والتضييق عليه، وتحويل مراكز ال
... Show MoreObesity is disorder in a foremost nutritional health it’s developed with countries developing. Also is known as increasingin fat accumulation that lead toproblem in health, besidesmay coin one of the reasons lead toloss of life,the obesity not effect on adults just but effect onoffspringand juveniles. In some ofinhabitants the incidence of obesity is superior in female than in male; on the other hand, the variation degree of the between the genderdifferby country.Obesity is generally measured by body mass index and waist circumference, Obesity are classified according to body mass index into:Pre obesity sort 1 : (25 - 29.9) kg/m2, Obesity sort 2 : (30 - 34.9 kg/m2) and extreme obesity sort 3: (40 kg/m2) or greater. Obesity is described by
... Show MoreCloud computing is a newly developed concept that aims to provide computing resources in the most effective and economical manner. The fundamental idea of cloud computing is to share computing resources among a user group. Cloud computing security is a collection of control-based techniques and strategies that intends to comply with regulatory compliance rules and protect cloud computing-related information, data apps, and infrastructure. On the other hand, data integrity is a guarantee that the digital data are not corrupted, and that only those authorized people can access or modify them (i.e., maintain data consistency, accuracy, and confidence). This review presents an overview of cloud computing concepts, its importance in many
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