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The intention of this work is to study a mathematical model for fractal-fractional tuberculosis and COVID-19 co-infection under the Atangana-Baleanu fractal-fractional operator. Firstly, we formulate the tuberculosis and COVID-19 co-infection model by considering the tuberculosis recovery individuals, the COVID-19 recovery individuals, and both disease recovery compartment in the proposed model. The fixed point approach is utilized to explore the existence and uniqueness of the solution in the suggested model. The stability analysis related to solve the Ulam-Hyers stability is also investigated. This paper is based on Lagrange's interpolation polynomial in the numerical scheme, which is validated through a specific case with a comparative numerical analysis for different values of the fractional and fractal orders.
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COVID-19 , Coinfection , Humans , Fractals , IntentionABSTRACT
Real-world applications process enormous amounts of data, especially in the area of large-dimension features. This work aims to present new classes of functions based on SM*-open sets that are a modification of simply open sets;namely, SM*-continuous, SM*-irresolute, proper continuous, SM*-open, SM*-closed, strongly SM*-irresolute, Pre SM*-irresolute, Pre SM*-open, super SM*-open and completely irresolute. The idea of fuzzy soft multifunction between fuzzy soft topological spaces, developed by Metin, is frequently used. Our current research project uses our suggested idea to introduce coronavirus application and infer the most important causal symptoms of coronavirus patients. Furthermore, we created an algorithm to demonstrate the applicability of our proposed technique based on the presented concept. Additionally, the results obtained using MATLAB programming. Finally, realistic WHO-compliant results were achieved for the most serious symptoms of coronavirus patients, as well as a suggested strategy that is competitive. Therefore, decision-making in the future needs to consider our suggestion. In order to promote the long-term wellbeing of both nature and humanity. Our proposed approach is reasonable and effective. The results showed that the methodology we used was reliable as it was consistent with World Health Organization publications.
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The oil industry is experiencing a critical situation as the Covid-19 pandemic outbreak. There are several challenges that facing the industry specially the investors as the global decline in demand for Energy merchandises, the future exploration and development drilling in new assets that require massive investments is still uncertain based on the current market price and conditions. The much-reported fall in oil prices and the acute pressure on IOCs to survive in this environment led the companies to stop many ongoing projects and shrink work profile that affected the oil production all over the world. The situation in Egypt is quite challenging for the investors as Egypt is a big consumer, along with the political stability that kept the economy running directed the big IOCs to embrace innovative approaches to lower the operating costs that has the direct impact on the cost per barrel to support maintaining the country growth and secure current energy demand. Dragon Oil company as newly introduced to Egypt's market after acquiring the market shares of one of the major joint ventures in Egypt (Gulf of Suez Petroleum Company- GUPCO) in October 2019 has faced the same dilemma of exerted pressure on the expenditures (Capex and Opex) in order to cope with the global market circumstances. However that didn't deter the company to embrace an innovative way of thinking and handling for the situation. Dragon Oil/GUPCO multi-disciplinary teams achieved successfully a production incremental increase of 10,000 barrels per day through the past six month by adapting a strategic management innovative plans, alternative lower cost technical solutions, production optimization and introducing new proved technologies to the 50 years old assets. This paper will highlight the complete workflow adopted by GUPCO/Dragon Oil teams covering the whole process aspects;appraise, select, define and execution phases to achieve the company goals. The work done was including restoring production from Shut-in offshore platforms or wells via fixing the surface network using neoteric solutions, widely applying rigless interventions using several new techniques in the current producers to maximize their production and optimizing the production cycle across the four production chokes In Summary, Dragon Oil/GUPCO teams managed to increase GUPCO's production despite of the restricted budget and the negative impact of COVID-19 pandemic on the oil price and reach an outstanding performance in operation excellence and safety aspects that results in arresting the natural decline and increase the growth production by about 15% from the 2019 Average production. Copyright © 2023, Society of Petroleum Engineers.
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Acute lower respiratory infection is a leading cause of death in developing countries. Hence, progress has been made for early detection and treatment. There is still a need for improved diagnostic and therapeutic strategies, particularly in resource-limited settings. Chest X-ray and computed tomography (CT) have the potential to serve as effective screening tools for lower respiratory infections, but the use of artificial intelligence (AI) in these areas is limited. To address this gap, we present a computer-aided diagnostic system for chest X-ray and CT images of several common pulmonary diseases, including COVID-19, viral pneumonia, bacterial pneumonia, tuberculosis, lung opacity, and various types of carcinoma. The proposed system depends on super-resolution (SR) techniques to enhance image details. Deep learning (DL) techniques are used for both SR reconstruction and classification, with the InceptionResNetv2 model used as a feature extractor in conjunction with a multi-class support vector machine (MCSVM) classifier. In this paper, we compare the proposed model performance to those of other classification models, such as Resnet101 and Inceptionv3, and evaluate the effectiveness of using both softmax and MCSVM classifiers. The proposed system was tested on three publicly available datasets of CT and X-ray images and it achieved a classification accuracy of 98.028% using a combination of SR and InceptionResNetv2. Overall, our system has the potential to serve as a valuable screening tool for lower respiratory disorders and assist clinicians in interpreting chest X-ray and CT images. In resource-limited settings, it can also provide a valuable diagnostic support.
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Introduction: COVID 19 pandemic has caused unprecedented devastation worldwide. Spectrum of Covid 19 illness is wide and variable. Risk of mortality is increased in chronic kidney disease patients, during coronavirus disease. CKD is an independent risk factor for poor outcome. AKI is also common in COVID-19 patients who are hospitalized. This study was undertaken to see the outcome of Covid-19 infection in CKD patients. Method(s): This retrospective observational study was carried out in the Kidney Foundation Hospital and Research Institute, Bangladesh from January 2021 to July 2022. One hundred CKD patients who were on regular follow up in the outpatient department and developed COVID-19 as confirmed by reverse transcription polymerase chain reaction (RT-PCR) test underwent chart review after they consented to be part of the study. Their clinical parameters, treatment regiments and laboratory investigations were noted in a data collection sheet. Data was analyzed by Statistical Analysis Software. Result(s): The mean age of the patients was 55.2 years. Of them 43% were female. Diabetes mellitus was the most common comorbidity, seen in 65% of the patients. 24% were CKD stage 4 or 5 prior to the onset of COVID-19, rest were of earlier stage. Hospitalization was required in 65.3% patients;41.1% required oxygen, steroid given in 19.8% patients,8.4% required ICU transfer. 7 patients died, all of respiratory failure. Treatment with antiviral, biologics like Tocilizumab and plasma exchange was not commonly done. AKI developed in 28% of the patients during the course of the illness. Males were more prone to develop AKI (p = 0.23). People with longer duration of symptoms had higher incidence of AKI (p < 0.0001). AKI incidence did not vary according to baseline eGFR (p = 0.16). Among those who developed AKI, 17.9% required temporary dialysis and 7.1% went on to develop end stage kidney disease. Interim outcomes such as hospitalization, oxygen requirement, ICU transfer and death did not vary according to development of AKI. Conclusion(s): People with chronic kidney disease and other comorbid conditions are at higher risk for more serious COVID-19 illness. In our study it has been shown that a significant proportion of CKD patients developed AKI after COVID 19 infection of which a number of patients develop end stage kidney disease and required renal replacement therapy. No conflict of interestCopyright © 2023
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Background In thoracic surgeries requiring thoracotomy incisions, correct positioning of the double-lumen endotracheal tube (DLT) is mandatory. After the pandemic of novel COVID-19, using simple, noninvasive technology such as lung ultrasound (LUS) can be important in avoiding the possibility of spreading infectious diseases or contagious infections that can follow using fiberoptic bronchoscopy (FOB). Objectives We aimed to assess the accuracy of auscultation and LUS in relation to FOB in the assessment of DLT placement and to identify the possibility of using LUS as an alternative to FOB during DLT insertion. Methods This diagnostic accuracy study was conducted according to STARD guidelines;enrolled 120 cases requiring DLT intubation. After DLT insertion, all patients were examined by stethoscope, then by LUS for determination of DLT position, and then confirmed by FOB in the same patient. Results Three patients dropped out due to failed intubation, and only 117 cases were analyzed. Time was significantly longer for LUS than for auscultation and FOB and was insignificantly different between auscultation and FOB. Auscultation had 76.14% sensitivity, 34.48% specificity, and 65.81% accuracy in the determination of correct DLT placement. LUS had 92.05% sensitivity, 79.31% specificity, and 88.89% accuracy in detecting correct DLT placement. There was substantial agreement between LUS and FOB (κ = 0.705) and poor agreement between auscultation and FOB (κ = 0.104). Conclusions LUS can be used as a simple, noninvasive tool for detecting DLT placement with a substantial agreement with FOB.
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OBJECTIVE: The purpose of this systematic review was to study the incidence, risk factors and patients subjected to Guillain-Barré syndrome (GBS) after COVID-19. MATERIALS AND METHODS: For qualitative assessment and assessing the methodological quality, the Cochrane Handbook for Systematic Reviews of Interventions and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) checklist were utilized. Data from PubMed, Cochrane, Embase, CINAHIL, Medline, ResearchGate, and Scopus were searched. The relevant studies involved patients with confirmed COVID-19 diagnosis by RT-PCR, and GBS diagnosis based on typical clinical symptoms and/or confirmatory diagnostic results. A total of 12 English relevant articles (6 papers were case reports and 8 were case series with a total of 32 patients) published in a peer-reviewed journal from 2019 to 2021 were included. Following the review methodology, two independent raters were responsible for retrieving, extracting and checking for data eligibility. Demographic characteristics are presented as frequencies and percentages. Based on distribution of values, continuous data were expressed as median and interquartile range (IQR). RESULTS: Out of 32 patients, 26 patients reported neurological symptoms, 6 cases went unnoticed, 7 cases showed involvement of the cranial nerves, 12 cases did not, and 13 cases went unreported. CONCLUSIONS: It is too early to draw any conclusions concerning a potential relationship between SARS-CoV-2 infection and GBS. More large-scale observational studies are required to understand the pathogenesis of SARS-CoV-2-associated GBS and to demonstrate a definite causal relationship between GBS and SARS-CoV-2 infection.
Subject(s)
COVID-19 , Guillain-Barre Syndrome , Humans , COVID-19/complications , COVID-19/epidemiology , SARS-CoV-2 , Guillain-Barre Syndrome/diagnosis , Guillain-Barre Syndrome/epidemiology , Guillain-Barre Syndrome/etiology , Incidence , COVID-19 TestingABSTRACT
Background: The COVID-19 pandemic has irreversibly altered the medical landscape. Compromised mental health among medical staff and the general population has called for new patient approaches, therapies, and medical services, among which Telehealth features prominently.Results: This paper discusses the structure, approach, and efficiencies of pandemic-related mental health services in Egypt and summarizes responses and initiatives launched by the government of Egypt. A particular focus on the Gen-eral Secretariat of Mental Health and Addiction Treatment (GSMHAT)'s action plan as well as Ain Shams University's hospital Okasha Institute of Psychiatry sheds light on localized responses to the pandemic's psychological impact.Conclusions: Data showcasing the several types of Telehealth employed are used to derive conclusions about the merits and challenges of emerging online treatments within the context of COVID-19.
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Background:After being released from the hospital, COVID-19 cases frequently report experiencing tiredness, dyspnea, muscle weakness, and mental agony. Method(s): The study involved 100 participants (both sexes, 30 to 50 years old) who had been COVID-19 for three to six months ago. A respiratory pressure meter was used to measure the highest possible inspiratory and expiratory pressures. A hand dynamometer was used to measure hand grip strength, while the Medical Outcomes Study Questionnaire Short Form 36 Health Survey was used to measure the quality of life (SF-36). Result(s): The results of Pearson correlation coefficients in post-Covid-19 cases showed a strong correlation between respiratory muscle strength and hand grip muscles. Additionally, respiratory muscle strength and hand grip strength had a significant impact on the quality of life of post-Covid-19 cases. (p <0.05). Conclusion(s): There was a correlation between the gripping power of the hands and the respiratory muscle strength in individuals who had undergone COVID-19 that in turn had effect on quality of life. This might aid in the efficient recovery of these patients. Copyright © 2022, Anka Publishers. All rights reserved.
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In the past few years, the world has suffered from an untreated infectious epidemic disease (COVID-19), caused by the so-called coronavirus, which was regarded as one of the most dangerous and viral infections. From this point of view, the major objective of this intended paper is to propose a new mathematical model for the coronavirus pandemic (COVID-19) outbreak by operating the Caputo fractional-order derivative operator instead of the traditional operator. The behavior of the positive solution of COVID-19 with the initial condition will be investigated, and some new studies on the spread of infection from one individual to another will be discussed as well. This would surely deduce some important conclusions in preventing major outbreaks of such disease. The dynamics of the fractional-order COVID-19 mathematical model will be shown graphically using the fractional Euler Method. The results will be compared with some other concluded results obtained by exploring the conventional model and then shedding light on understanding its trends. The symmetrical aspects of the proposed dynamical model are analyzed, such as the disease-free equilibrium point and the endemic equilibrium point coupled with their stabilities. Through performing some numerical comparisons, it will be proved that the results generated from using the fractional-order model are significantly closer to some real data than those of the integer-order model. This would undoubtedly clarify the role of fractional calculus in facing epidemiological hazards.
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Today, automatic food/non-food classification became extremely important for many real-time applications, specifically since the pandemic of the COVID-19 virus. Such that the 'no food policy' now became applied more than ever to help decrease the spread of the COVID-19 virus. Consequently, many studies used deep neural networks for the food/non-food classification task, yet these deep neural networks were computationally expensive. As a result, in this paper, a lightweight Convolution Neural Network (CNN) is proposed and put into use for classifying foods and non-foods. Compared to prior efforts, this work yields an outperforming result with an accuracy of 96.875%. © 2022 IEEE.
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This study empirically examines the spillovers from global uncertainties to the sectoral indices of the Pakistan stock market (PSX). Furthermore, we select three major sectoral indices, i.e., the energy, financial, and material composite indices. These indices represent a massive capital volume of PSX. We utilize the data from 10 May 2002 to 27 June 2022 to examine the outbreak due to the global financial crisis (GFC) of 2007-2008 and the impact of the world's great pandemic, of COVID-19. Additionally, we applied a novel econometric estimation approach: quantile connectedness. We found that connectedness is strong in the case of highly positive changes (above the 20% quantile) and highly negative changes (below the 80% quantile). Additionally, the study also found that materials sector is the least connected at level of 1.58%. In contrast, the financial sector was a strong transmitter of spillovers during the entire study period at connectedness of 54.59%. Regarding graphical results, we found that economic policy uncertainty (EPU) and crude oil index (WTI) are net transmitters, especially during the financial crisis and COVID-19, whereas WTI transmitting impact was significantly dominant during GFC 2007-2008. Conversely, the index MSCI remains the recipient of the spillover during the entire study period, where the remitting effect was observed as dominant during the GFC, and COVID-19 outbreak. The energy sector was found to be more recipient during the GFC, with additional turn transmitters of the shocks after the COVID-19 pandemic. The study recommends that portfolio managers and individual investors consider the materials sector for their investment due to the least connectivity. Similarly, investors need to invest carefully in the financial sector because it is a net transmitter of spillovers to other sectors.
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Background: In thoracic surgeries requiring thoracotomy incisions, correct positioning of the double-lumen endotracheal tube (DLT) is mandatory. After the pandemic of novel COVID-19, using simple, noninvasive technology such as lung ultrasound (LUS) can be important in avoiding the possibility of spreading infectious diseases or contagious infections that can follow using fiberoptic bronchoscopy (FOB). Objectives: We aimed to assess the accuracy of auscultation and LUS in relation to FOB in the assessment of DLT placement and to identify the possibility of using LUS as an alternative to FOB during DLT insertion. Methods: This diagnostic accuracy study was conducted according to STARD guidelines; enrolled 120 cases requiring DLT intubation. After DLT insertion, all patients were examined by stethoscope, then by LUS for determination of DLT position, and then confirmed by FOB in the same patient. Results: Three patients dropped out due to failed intubation, and only 117 cases were analyzed. Time was significantly longer for LUS than for auscultation and FOB and was insignificantly different between auscultation and FOB. Auscultation had 76.14% sensitivity, 34.48% specificity, and 65.81% accuracy in the determination of correct DLT placement. LUS had 92.05% sensitivity, 79.31% specificity, and 88.89% accuracy in detecting correct DLT placement. There was substantial agreement between LUS and FOB (κ = 0.705) and poor agreement between auscultation and FOB (κ = 0.104). Conclusions: LUS can be used as a simple, noninvasive tool for detecting DLT placement with a substantial agreement with FOB.
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Computational tools in investigating of spectral heterocyclic compounds ranges based on pyrimidine2thiones, take some importance in identifying their molecular and electronic behavior. Some charcoal heterocyclic compounds were previously synthesized in our laboratory and their experimental results were compared with the computational evaluation. Computational spectroscopic analytical items (IR, NMR and UV-Vis) were calculated using the more popular DFT methods and the predicted results were compared with the reported experimental ones. Quantum and chemical parameters were calculated and molecular electrostatic surface potential (MEP) was studied which predicted the highly electronic sites around the compounds. Some molecular properties (ionization energy, electron affinity, energy gap, hardness, electronegativity, electrophilicity index, static dipole moment and average linear polarizability) of these Schiff bases which were computed at B3LYP/6-31G(d,p) level in aqueous phase. Benchmark analysis was performed for three ab initio functionals such B3LYP, BPV86 and B3PW91 methods to explain the data resulted from NMR spectra. The docking study of some selected previously synthesized compounds was performed using the viral Mpro enzyme protein in compared to a k36 reference ligand inhibitor. The study indicated the ability of the synthesized compounds to form H-bond and hydrophobic (VDW, π-alkyl and π-sulfur) interactions with Mpro enzyme receptor with high inhibition effect of compound L2.
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A novel series of bis-[1,3,4]thiadiazolimines, and bis-thiazolimines, with alkyl linker, were synthesized through general routes from cyclization of 1,1'-(hexane-1,6-diyl)bis(3-phenylthiourea) and hydrazonoyl halides or α-haloketones, respectively. Docking studies were applied to test the binding affinity of the synthesized products against the Mpro of SARS-CoV-2. The best compound, 5h, has average binding energy (-7.50 ± 0.58 kcal/mol) better than that of the positive controls O6K and N3 (-7.36 ± 0.34 and -6.36 ± 0.31 kcal/mol). Additionally, the docking poses (H-bonds and hydrophobic contacts) of the tested compounds against the Mpro using the PLIP web server were analyzed.
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A novel series of bis- (Abdelhamid et al., 2017, Banerjee et al., 2018, Bharanidharan et al., 2022)thiadiazoles was synthesized from the reaction of precursor dimethyl 2,2'-(1,2-diphenylethane-1,2-diylidene)-bis(hydrazine-1-carbodithioate) and hydrazonyl chlorides in ethanol under ultrasonic irradiation. Spectral tools (IR. NMR, MS, elemental analyses, molecular dynamic simulation, DFT and LUMO and HOMO) were used to elucidate the structure of the isolated products. Molecular docking for the precursor, 3 and ligands 6a-i to two COVID-19 important proteins Mpro and RdRp was compared with two approved drugs, Remdesivir and Ivermectin. The binding affinity varied between the ligands and the drugs. The highest recorded binding affinity of 6c with Mpro was (-9.2 kcal/mol), followed by 6b and 6a, (-8.9 and -8.5 kcal/mol), respectively. The lowest recorded binding affinity was (-7.0 kcal/mol) for 6 g. In comparison, the approved drugs showed binding affinity (-7.4 and -7.7 kcal/mol), for Remdesivir and Ivermectin, respectively, which are within the range of the binding affinity of our ligands. The binding affinity of the approved drug Ivermectin against RdRp recoded the highest (-8.6 kcal/mol), followed by 6a, 6 h, and 6i are the same have (-8.2 kcal/mol). The lowest reading was found for compound 3 ligand (-6.3 kcal/mol). On the other side, the amino acids also differed between the compounds studied in this project for both the viral proteins. The ligand 6a forms three H-bonds with Thr 319(A), Sr 255(A) and Arg 457(A), whereas Ivermectin forms three H-bonds with His 41(A), Gly143(A) and Gln 18(A) for viral Mpro. The RdRp amino acids residues could be divided into four groups based on the amino acids that interact with hydrogen or hydrophobic interactions. The first group contained 6d, 6b, 6 g, and Remdesivir with 1-4 hydrogen bonds and hydrophobic interactions 1 to 10. Group 2 is 6a and 6f exhibited 1 and 3 hydrogen bonds and 15 and 14 hydrophobic interactions. Group 3 has 6e and Ivermectin shows 4 and 3 hydrogen bonds, respectively and 11 hydrophobic interactions for both compounds. The last group contains ligands 3, 6c, 6 h, and 6i gave 1-3 hydrogen bonds and 6c and 3 recorded the highest number of hydrophobic interactions, 14 for both 6c and 6 h. Pro Tox-II estimated compounds' activities as Hepatoxic, Carcinogenic and Mutagenic, revealing that 6f-h were inactive in all five similar to that found with Remdesivir and Ivermectin. The drug-likeness prediction was carried out by studying physicochemical properties, lipophilicity, size, polarity, insolubility, unsaturation, and flexibility. Generally, some properties of the ligands were comparable to that of the standards used in this study, Remdesivir and Ivermectin.
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Recently, no one can deny the importance of distributed generation (DG). The tendency toward using DG in electrical generation networks is increasing rapidly. In addition to the positive aspects, the ecological, economic, and technical advantages of connecting DG units to distribution networks, the location and the size of the DG unit are important factors for these advantages. For this purpose, a novel method of optimal apportionment and sizing when introducing DG is presented, based on the curtailment of the SPP (simple payback period). This can be achieved through the use of the IEEE 33 bus system and optimization techniques such as Grey Wolves, Grey Wolves with Cauchy equation, and Coronavirus techniques that help determine the location and size of generators in the distribution network. In this paper, we aim to present a thorough study on the impact of the DG units, when connected to distribution networks, based on the economical viewpoint using MATLAB software. © 2022 IEEE.
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Waning immunity following administration of mRNA-based COVID-19 vaccines remains a concern for many health systems. We undertook a study to determine if recent reports of waning for severe disease could have been attributed to design-related bias by conducting a study only among those detected with a first SARS-CoV-2 infection. We used a matched case-control study design with the study base being all individuals with first infection with SARS-CoV-2 reported in the State of Qatar between 1 January 2021 and 20 February 2022. Cases were those detected with first SARS-CoV-2 infection requiring intensive care (hard outcome), while controls were those detected with first SARS-CoV-2 infection who recovered without the need for intensive care. Cases and controls were matched in a 1:30 ratio for the calendar month of infection and the comorbidity category. Duration and magnitude of conditional vaccine effectiveness against requiring intensive care and the number needed to vaccinate (NNV) to prevent one more case of COVID-19 requiring intensive care was estimated for the mRNA (BNT162b2/mRNA-1273) vaccines. Conditional vaccine effectiveness against requiring intensive care was 59% (95% confidence interval (CI), 50 to 76) between the first and second dose, and strengthened to 89% (95% CI, 85 to 92) between the second dose and 4 months post the second dose in persons who received a primary course of the vaccine. There was no waning of vaccine effectiveness in the period from 4 to 6, 6 to 9, and 9 to 12 months after the second dose. This study demonstrates that, contrary to mainstream reports using hierarchical measures of effectiveness, conditional vaccine effectiveness against requiring intensive care remains robust till at least 12 months after the second dose of mRNA-based vaccines.
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In the context of the COVID-19 pandemic in 2020, education experienced the direct transition to digitalisation at the international level, and academic studies migrated to the virtual environment. According to official UNESCO data presented by Statistics, 23rd March 2020, [1], more than 1.5 billion students globally have been affected by partial or total closure of educational institutions. (Statistics, Mar 2020) With the closure of schools, both students and teachers started the journey to the New Education - The Online School. But the main problem was yet to be assessed as “children are not the face of the pandemic.” [2]. Thus, a couple of questions were asked to mitigate the implications of the official governmental decision, understanding the assessment of digital educational preparedness and examples of activities conducted that led children of four nations to be inspired by Space Scientists and engineers. From spending an average of 2 to 4 hours a day in the digital environment, to perform homework and use social media channels, the direct time added for The Online School has doubled and even tripled. On average, children started to use computers for over 10 – 12 hours. As a result, vulnerability and differences increased, access to quality education has decreased considerably due to weak computer skills, but the essential fact studied has been the activities conducted to keep children engaged in their educational development. However, whether we are talking about the connection between pupil-pupil or pupil-teacher, or the ability to continue extracurricular activities in the digital environment, there was a lack of consultation and involvement of students in the decision-making process and a lack of creating interactive projects and dedicated support on behalf of authorities. Copyright © 2021 by the authors. Published by the IAF, with permission and released to the IAF to publish in all forms.