Background:Measurement of hemoglobin A1c (A1C) is a renowned tactic for gauging long-term glycemic control, and exemplifies an outstanding influence to the quality of care in diabetic patients.The concept of targets is open to criticism; they may be unattainable, or limit what could be attained, and in addition they may be economically difficult to attain. However, without some form of targeted control of an asymptomatic condition it becomes difficult to promote care at allObjectives: The present article aims to address the most recent evidence-based global guidelines of A1C targets intended for glycemic control in Type 2 Diabetes Mellitus (T2D).Key messages:Rationale for Treatment Targets of A1C includesevidence for microvascular and macrovascular protectionand changes in quality of life. More or less stringent A1C goals may be appropriate for individual patients, andgoals should be individualized based on:duration of diabetes, age/life expectancy, comorbid conditions, CVD or advanced microvascular complications,hypoglycemia unawareness, and individual patient considerations
The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t
... Show MoreRecent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T
... Show MoreCryptography is a major concern in communication systems. IoE technology is a new trend of smart systems based on various constrained devices. Lightweight cryptographic algorithms are mainly solved the most security concern of constrained devices and IoE systems. On the other hand, most lightweight algorithms are suffering from the trade-off between complexity and performance. Moreover, the strength of the cryptosystems, including the speed of the algorithm and the complexity of the system against the cryptanalysis. A chaotic system is based on nonlinear dynamic equations that are sensitive to initial conditions and produce high randomness which is a good choice for cryptosystems. In this work, we proposed a new five-dimensional of a chaoti
... Show MoreBackground: the aim of this study was to assess the 2-year pulp survival of deep carious lesions in teeth excavated using a self-limiting protocol in a single-blind randomized controlled clinical trial. Methods: At baseline, 101 teeth with deep carious lesions in 86 patients were excavated randomly using self-limiting or control protocols. Standardized clinical examination and periapical radiographs of teeth were performed after 1- and 2-year follow-ups (REC 14/LO/0880). Results: During the 2-year period of the study, 24 teeth failed (16 and 8 at T12 and T24, respectively). Final analysis shows that 39/63 (61.9%) of teeth were deemed successful (16/33 (48.4%) and 23/30 (76.6%) in the control and experimental groups, respectively wit
... Show MoreSignificant advancements in nanoscale material efficiency optimization have made it feasible to substantially adjust the thermoelectric transport characteristics of materials. Motivated by the prediction and enhanced understanding of the behavior of two-dimensional (2D) bilayers (BL) of zirconium diselenide (ZrSe2), hafnium diselenide (HfSe2), molybdenum diselenide (MoSe2), and tungsten diselenide (WSe2), we investigated the thermoelectric transport properties using information generated from experimental measurements to provide inputs to work with the functions of these materials and to determine the
A Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co2+, Ni2+, Cu2+) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)2] Cl2, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.
The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
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