Photovoltaic devices (PVs) were fabricated by spray-coating an ink of copper indium diselenide CuInSeR 2 R(CIS) nanocrystals as the light-absorbing layer. Without high-temperature post-deposition annealing, PVs were made on glass substrates with power conversion efficiencies of up to 1.5% and 0.9%, for Au and Mo coated respectively, under AM 1.5 illumination. UV–Vis spectrophotometer in the wavelength range 350–1500 nm. X-ray diffraction (XRD) and energy dispersive spectroscopy (EDS) analysis it is evident that CuInSeR 2 R have the chalcopyrite structure as the major phase and no secondary phase with a preferred orientation along (112) direction and The atomic ratio of Cu : In : Se in the nanocrystals is nearly 1 : 1 : 2.

beef and chicken meat were used to get Sarcoplasim, the chicken Sarcoplasim were used to prepare antibody for it after injected in rabbit, the antiserums activity were 1/32 by determined with Immune double diffusion test, the self test refer to abele for some antiserums to detected with beef sarcoplasim, which it mean found same proteins be between beef and chicken meat, which it refer to difficult depended on this immune method to detect for cheat of chicken meat with beef, so the antibody for beef sarcoplasim were removed from serum by immune absorption step to produce specific serum against chicken sarcoplasim that it used in Immune double diffusion test to qualitative detect for cheat beef with 5% chicken meat or more at least, and the

Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

Abstract The goal of current study was to identify the relationship between addiction of self-images (Selfie) and personality disorder of narcissus, and the difference of significance the relationship between addiction self-images (selfie) and personality disorder narcissus at students of Mustansiriya university, addiction self- images (selfie) defined: a photograph that one has taken of oneself, typically one taken with a smartphone or webcam and shared via social media, edit and down lowed to social networking sites, and over time, the replacement of normal life virtual world, which is accompanied by a lack of a sense of time, and the formation of repeated patterns increase the risk of social and personal problems. To achieve the goals

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

The primary objective of this research be to develop a novel thought of fibrewise micro—topological spaces over B. We present the notions from fibrewise micro closed, fibrewise micro open, fibrewise locally micro sliceable, and fibrewise locally micro-section able micro topological spaces over B. Moreover, we define these concepts and back them up with proof and some micro topological characteristics connected to these ideas, including studies and fibrewise locally micro sliceable and fibrewise locally micro-section able micro topological spaces, making it ideal for applications where high-performance processing is needed. This paper will explore the features and benefits of fibrewise locally micro-sliceable and fibrewise locally