Difficulties In Management Research Articles

Challenges faced by final year dental students and house officers while performing endodontic treatment.

Objective: To identify the challenges faced by final year dental students and house officers while performing endodontic treatment. Study Design: Cross sectional study. Setting: Multicenter study. Setting: Involving Dental Colleges of Twin Cities Dental Hospitals of Islamabad and Rawalpindi including Islamabad Dental Hospital, Islamic International Dental Hospital, Pakistan Institute of Medical Sciences, Armed Forces Institute of Dentistry, Rawal Institute of Health Sciences and Margalla Institute of Health Sciences. Period: June 2023 to December 2023. Material & Methods: This cross sectional descriptive study was conducted on 263 participants. The inclusion criteria was final year dental students and house officers who had completed their mandatory rotation in endodontics department and performed root canal treatment with conventional methods. A structured questionnaire consisting of five sections containing patient management, access opening, working length determination, cleaning and shaping procedure and obturation was constructed. Google forms were sent to the participants after sample size was calculated with WHO calculator. Data was analyzed through Google forms. Results: The current study shows that majority of the participants faced difficulties in the patient management and obturation procedure. The overall most common difficulty encountered was rubber dam application (44.1%) followed by accessory GP bending during obturation (42%), apex locator use (39.4%), and canal orifice location (39.8%). Conclusion: The students and house officers are facing multiple difficulties in performing root canal treatment independently. Therefore there is a need to focus more on the training of students and house officers in their endodontic department rotation.

Accounting journal entries as a long‐term multivariate time series: Forecasting wholesale warehouse output

AbstractLess than 2 years ago, many small entrepreneurs in the commodities trading business faced price volatility, which had not been the case for the last few decades. Generally, the income section of the profit and loss statement was not the main problem, especially in building material commodities trading, due to the recent growth in real estate demand. Logistic disorders, raw material shortages, inflation, and interest rate growth caused difficulties in supply management and warehouse balancing, which were reflected in a particular significant expense called the cost of goods sold. The real problem of its forecasting was identified, and data from accounting books likely contain information about previous warehouse dynamics. This paper presents how accounting data are prepared and shaped into time series suitable for machine learning algorithms, the relevant literature that helped in algorithm selection, and the development and description of the forecasting model, as well as its benchmarking with traditional forecasting models. Visualization and mean squared error loss measured on unseen data show that the model has proven more successful than expected. Based on data from four journal accounts spanning over 14 years, the model predicts the debit and credit sides of the wholesale warehouse for 150 working days.

Application of Module Level Power Electronics Technology in Distributed Photovoltaic Power Generation System

Distributed photovoltaic power generation system usually adopts series wiring scheme, which has problems such as high voltage DC electrical safety risk, power mismatch of modules and maintenance management difficulty. Three schemes of module level power electronics technology are proposed, including string inverter with rapid shutdown device, string inverter with module optimizer and micro inverter. The electrical shut-off, power generation data monitoring, power optimization and inverter function characteristics of each scheme are described and compared, and the suggested application scenarios are given. In addition, typical electrical topology schemes of module level power electronic devices including rapid shutdown device, module optimizer and micro inverter are introduced.

Research on Intelligent Supervision System and Terminal for Small Sluice Group

As a conventional water conservancy project, small water gates play a crucial role in flood prevention and drainage, water storage and irrigation. In response to the problems of a large number, wide distribution, and difficult management of small water gates, this article proposes an intelligent supervision system for small water gate groups based on the three-level architecture of provinces, cities, and counties. Then, according to the requirements of small water gate supervision, the hardware circuit and software program of the monitoring terminal were specially designed. The main content of this article includes three aspects: the provincial, city, and county level design of regulatory platforms, the modular and hierarchical structure design of terminal hardware, and the standardization and standardization design of terminal software. It provides a solution for the intelligent, efficient, and standardized management of small water gate groups, as well as a low-cost, reliable, and versatile monitoring terminal for the implementation of the solution. It has positive significance in solving the management difficulties of small water gates.

Credit Risk Modelling

Abstract: Modern society recognizes the significance of Identity and Access Management. It's the method through which information is controlled in terms of who gets access to what and when. Creation of user and system identities is an IAM activity. Data and information sharing relies heavily on safe user access. In addition, most businesses are realizing the growing value of electronic data. Strong authentication is a common solution to this problem and is becoming more and more necessary as the standards for access protection rise. The two most critical IAM concepts that must be handled by the business are identity and access. More and more businesses are turning to an automated system to handle these tasks. But it opens up a new danger. Since these technologies lack the wit to make judgements on their own, we must supplement them with our own brainpower employing a variety of data mining algorithms. This allows us to save data for later model building. Everything you need to know about the difficulties of Identity and Access Management may be found in this document. A potential answer is provided for these problems.

Identity and Access Management: Concept, Challenges, Solutions A Small Snapshot Review

Abstract: Modern society recognizes the significance of Identity and Access Management. It's the method through which information is controlled in terms of who gets access to what and when. Creation of user and system identities is an IAM activity. Data and information sharing relies heavily on safe user access. In addition, most businesses are realizing the growing value of electronic data. Strong authentication is a common solution to this problem and is becoming more and more necessary as the standards for access protection rise. The two most critical IAM concepts that must be handled by the business are identity and access. More and more businesses are turning to an automated system to handle these tasks. But it opens up a new danger. Since these technologies lack the wit to make judgements on their own, we must supplement them with our own brainpower employing a variety of data mining algorithms. This allows us to save data for later model building. Everything you need to know about the difficulties of Identity and Access Management may be found in this document. A potential answer is provided for these problems.

Teachers’ Continuous Professional Development through Lesson Study: Voices of Vietnamese EFL Teachers at University

This study investigated how teachers perceived the benefits and difficulties of implementing a Lesson Study (LS) in the context of English language teaching at a university in Vietnam. The data were collected from six teachers through semi-structured interviews. To analyze the data, two addressing themes (teachers’ perceived benefits and teachers’ perceived difficulties) were focused on while implementing LS. The results generally showed that the teachers believed that LS brought them three benefits: encouraging teachers’ exchange activities and helping them deepen knowledge of lesson content, understanding students’ learning activities and working processes, and promoting teachers’ motivation in pursuing their continuous professional development (CPD). Regarding teachers’ perceived difficulties in LS implementation, they reported lacking confidence in actively implementing LS activities. Additionally, they had difficulties in time management and encountered problems reaching a consensus for joint work due to the influence of muti-faceted aspects. Accordingly, the study provides pedagogical implications for related stakeholders (teachers, students, and policymakers) regarding LS implementation issues contributing to the success of LS implementation in Vietnam and other similar contexts.

Time in Range, Time in Tight Range, and Average Glucose Relationships Are Modulated by Glycemic Variability: Identification of a Glucose Distribution Model Connecting Glycemic Parameters Using Real-World Data.

Background: Time in range (TIR), time in tight range (TITR), and average glucose (AG) are used to adjust glycemic therapies in diabetes. However, TIR/TITR and AG can show a disconnect, which may create management difficulties. We aimed to understand the factors influencing the relationships between these glycemic markers. Materials and Methods: Real-world glucose data were collected from self-identified diabetes type 1 and type 2 diabetes (T1D and T2D) individuals using flash continuous glucose monitoring (FCGM). The effects of glycemic variability, assessed as glucose coefficient of variation (CV), on the relationship between AG and TIR/TITR were investigated together with the best-fit glucose distribution model that addresses these relationships. Results: Of 29,164 FCGM users (16,367 T1D, 11,061 T2D, and 1736 others), 38,259 glucose readings/individual were available. Comparing low and high CV tertiles, TIR at AG of 150 mg/dL varied from 80% ± 5.6% to 62% ± 6.8%, respectively (P < 0.001), while TITR at AG of 130 mg/dL varied from 65% ± 7.5% to 49% ± 7.0%, respectively (P < 0.001). In contrast, higher CV was associated with increased TIR and TITR at AG levels outside the upper limit of these ranges. Gamma distribution was superior to six other models at explaining AG and TIR/TITR interactions and demonstrated nonlinear interplay between these metrics. Conclusions: The gamma model accurately predicts interactions between CGM-derived glycemic metrics and reveals that glycemic variability can significantly influence the relationship between AG and TIR with opposing effects according to AG levels. Our findings potentially help with clinical diabetes management, particularly when AG and TIR appear mismatched.

Transient chemical and structural changes in graphene oxide during ripening

Graphene oxide (GO)—the oxidized form of graphene—is actively studied in various fields, such as energy, electronic devices, separation of water, materials engineering, and medical technologies, owing to its fascinating physicochemical properties. One major drawback of GO is its instability, which leads to the difficulties in product management. A physicochemical understanding of the ever-changing nature of GO can remove the barrier for its growing applications. Here, we evidencde the presence of intrinsic, metastable and transient GO states upon ripening. The three GO states are identified using a π−π*\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi -{\\pi }^{*}$$\\end{document} transition peak of ultraviolet–visible absorption spectra and exhibit inherent magnetic and electrical properties. The presence of three states of GO is supported by the compositional changes of oxygen functional groups detected via X-ray photoelectron spectroscopy and structural information from X-ray diffraction analysis and transmission electron microscopy. Although intrinsic GO having a π−π*\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\pi -{\\pi }^{*}$$\\end{document} transition at 230.5 ± 0.5 nm is stable only for 5 days at 298 K, the intrinsic state can be stabilized by either storing GO dispersions below 255 K or by adding ammonium peroxydisulfate.

Physical activity improves stress load, recovery, and academic performance-related parameters among university students: a longitudinal study on daily level

BackgroundPhysical activity has been proven to be beneficial for physical and psychological health as well as for academic achievement. However, especially university students are insufficiently physically active because of difficulties in time management regarding study, work, and social demands. As they are at a crucial life stage, it is of interest how physical activity affects university students' stress load and recovery as well as their academic performance.MethodsStudent´s behavior during home studying in times of COVID-19 was examined longitudinally on a daily basis during a ten-day study period (N = 57, aged M = 23.5 years, SD = 2.8, studying between the 1st to 13th semester (M = 5.8, SD = 4.1)). Two-level regression models were conducted to predict daily variations in stress load, recovery and perceived academic performance depending on leisure-time physical activity and short physical activity breaks during studying periods. Parameters of the individual home studying behavior were also taken into account as covariates.ResultsWhile physical activity breaks only positively affect stress load (functional stress b = 0.032, p < 0.01) and perceived academic performance (b = 0.121, p < 0.001), leisure-time physical activity affects parameters of stress load (functional stress: b = 0.003, p < 0.001, dysfunctional stress: b = -0.002, p < 0.01), recovery experience (b = -0.003, p < 0.001) and perceived academic performance (b = 0.012, p < 0.001). Home study behavior regarding the number of breaks and longest stretch of time also shows associations with recovery experience and perceived academic performance.ConclusionsStudy results confirm the importance of different physical activities for university students` stress load, recovery experience and perceived academic performance in home studying periods. Universities should promote physical activity to keep their students healthy and capable of performing well in academic study: On the one hand, they can offer opportunities to be physically active in leisure time. On the other hand, they can support physical activity breaks during the learning process and in the immediate location of study.

A Quasi-Experimental Study Investigating the Impact of a Lifestyle Redesign Program on the Well-Being of Korean University Students.

Korean university students (KUS) face numerous challenges that can jeopardize their well-being, including academic stress, peer pressure, irregular sleep patterns, unhealthy eating habits, lack of physical exercise, and difficulties in time management, resulting in unhealthy habits and fluctuations in lifestyle. Consequently, there is a growing need for interventions tailored to this population. This study explored the effects of a Lifestyle Redesign (LR) intervention on Korean university students' well-being including occupational participation, satisfaction, perceived stress levels, and quality of life. A quasi-experimental study with 33 KUS (17 intervention, 16 control) assessed the effects of a 10-week LR intervention on well-being of the students. Pre- and postintervention changes were measured using Canadian Occupational Performance Measure (COPM), Stress Response Inventory (SRI), and World Health Organization Quality of Life Scale Abbreviated Version (WHOQOL-BREF). The intervention, delivered by trained OTs, comprised of individual and group sessions. Statistically significant improvement was observed in occupational performance. While statistical significance was not consistently achieved in the rest of other areas, the LR group displayed positive trends. The LR group exhibited higher COPM satisfaction scores, lower SRI scores (indicating reduced stress), and elevated WHOQOL-BREF scores compared to the control group. This study contributes to the understanding of the importance of addressing lifestyle changes and habits in the well-being of university students, especially in the context of academic stress and peer pressure. Future research with larger, more diverse samples and extended intervention periods may offer further insights into the benefits of LR programs in university settings.

Lymphadenopathy Presenting as Rosai- Dorfman- Destombes Disease: A Rare Case Report

Rosai-Dorfman-Destombes disease is a very rare benign disorder of histiocyte proliferation with unknown etiology. We report the case of a 41 years old man diagnose with this disease, having had long standing cervical lymphadenopathy increasing in size. This case is presented given the difficulty in diagnosis and surgical management on skin involvement.

Epidemiology and Treatment of Surgical Infection after Ankle Arthroscopy: A Systematic Review.

Background: Ankle arthroscopy is indicated for both diagnosis and treatment of a large spectrum of common ankle disorders. It has certain advantages over the open procedure; however, it is important to recognize that there are some complications associated with it. Infections after this procedure are quite uncommon, with an overall estimated incidence of 2%. Given the low incidence of infections after ankle arthroscopy, not a great deal of literature on the topic has been published. The present review aims to provide an overview of the incidence, diagnosis, and treatment of infections after ankle arthroscopy. Methods: A systematic review of the literature indexed in the PubMed, MEDLINE, and Cochrane Library databases using search term "ankle arthroscopy infections" was performed in November 2023. No restrictions were applied concerning the date of publication. The Preferred reporting items for systematic reviews and meta-analyses (PRISMA) were followed. Among all surgical operations for the treatment of ankle and foot pathologies, we included articles with a described superficial or deep infection after ankle arthroscopy. Results: The search resulted in 201 studies. Only 21 studies met our inclusion criteria, and they were included in this systematic review. We evaluated 1706 patients who underwent 1720 arthroscopic tibiotalar procedures at an average age of 42 years old. Out of the 1720 procedures, 41 (2%) were complicated by infection. We divided infectious complications into superficial (68%; 28/41) and deep (32%; 13/41) infections. The most common pathogen isolated was Staphylococcus aureus. Arthroscopic arthrodesis was found to be the most affected by deep infections. Conclusions: Infection after ankle arthroscopy is an uncommon complication. Superficial infections were successfully treated with antibiotics, while surgical debridement, arthroscopic drainage, and intravenous antibiotics were necessary in cases of deep infections. Considering the amount of information on pathogens associated with knee and shoulder infections, there is still a lack of literature on pathogens associated with ankle infections, which makes their management difficulty.

Automated Identification of Sensitive Financial Data Based on the Topic Analysis

Data governance is an extremely important protection and management measure throughout the entire life cycle of data. However, there are still data governance issues, such as data security risks, data privacy breaches, and difficulties in data management and access control. These problems lead to a risk of data breaches and abuse. Therefore, the security classification and grading of data has become an important task to accurately identify sensitive data and adopt appropriate maintenance and management measures with different sensitivity levels. This work started from the problems existing in the current data security classification and grading work, such as inconsistent classification and grading standards, difficult data acquisition and sorting, and weak semantic information of data fields, to find the limitations of the current methods and the direction for improvement. The automatic identification method of sensitive financial data proposed in this paper is based on topic analysis and was constructed by incorporating Jieba word segmentation, word frequency statistics, the skip-gram model, K-means clustering, and other technologies. Expert assistance was sought to select appropriate keywords for enhanced accuracy. This work used the descriptive text library and real business data of a Chinese financial institution for training and testing to further demonstrate its effectiveness and usefulness. The evaluation indicators illustrated the effectiveness of this method in the classification of data security. The proposed method addressed the challenge of sensitivity level division in texts with limited semantic information, which overcame the limitations on model expansion across different domains and provided an optimized application model. All of the above pointed out the direction for the real-time updating of the method.

Optimizing dynamic economic dispatch through an enhanced Cheetah-inspired algorithm for integrated renewable energy and demand-side management

This study presents the Enhanced Cheetah Optimizer Algorithm (ECOA) designed to tackle the intricate real-world challenges of dynamic economic dispatch (DED). These complexities encompass demand-side management (DSM), integration of non-conventional energy sources, and the utilization of pumped-storage hydroelectric units. Acknowledging the variability of solar and wind energy sources and the existence of a pumped-storage hydroelectric system, this study integrates a solar-wind-thermal energy system. The DSM program not only enhances power grid security but also lowers operational costs. The research addresses the DED problem with and without DSM implementation to analyze its impact. Demonstrating effectiveness on two test systems, the suggested method's efficacy is showcased. The recommended method's simulation results have been compared to those obtained using Cheetah Optimizer Algorithm (COA) and Grey Wolf Optimizer. The optimization results indicate that, for both the 10-unit and 20-unit systems, the proposed ECOA algorithm achieves savings of 0.24% and 0.43%, respectively, in operation costs when Dynamic Economic Dispatch is conducted with Demand-Side Management (DSM). This underscores the advantageous capability of DSM in minimizing costs and enhancing the economic efficiency of the power systems. Our ECOA has greater adaptability and reliability, making it a promising solution for addressing multi-objective energy management difficulties within microgrids, particularly when demand response mechanisms are incorporated. Furthermore, the suggested ECOA has the ability to elucidate the multi-objective dynamic optimal power flow problem in IEEE standard test systems, particularly when electric vehicles and renewable energy sources are integrated.

Suspected Mal de Debarquement Syndrome: A Case Report Highlighting the Difficulty in Diagnosis and Management.

MdDS is syndrome of oscillating vertigo following cessation of passive motion. The pathogenesis of this disorder is not well understood, but functional imaging studies suggest cortical connectivity dysfunction in feedback loops of the vestibulo-ocular system and visuo-spatial system. Patients go through multiple appointments and often specialist referrals before being diagnosed. After diagnosis, optimal management is difficult. Several treatment modalities, including medication, vestibular rehabilitation, and neuromodulation, have had variable success in management. We present the case of a young, female active duty Air Force Captain who developed symptoms while deployed. She underwent multiple treatments with variable success. Her clinical course highlights the difficulties for patients and providers posed by suspected MdDS.

Multi-Stage Learning Framework Using Convolutional Neural Network and Decision Tree-Based Classification for Detection of DDoS Pandemic Attacks in SDN-Based SCADA Systems

Supervisory Control and Data Acquisition (SCADA) systems, which play a critical role in monitoring, managing, and controlling industrial processes, face flexibility, scalability, and management difficulties arising from traditional network structures. Software-defined networking (SDN) offers a new opportunity to overcome the challenges traditional SCADA networks face, based on the concept of separating the control and data plane. Although integrating the SDN architecture into SCADA systems offers many advantages, it cannot address security concerns against cyber-attacks such as a distributed denial of service (DDoS). The fact that SDN has centralized management and programmability features causes attackers to carry out attacks that specifically target the SDN controller and data plane. If DDoS attacks against the SDN-based SCADA network are not detected and precautions are not taken, they can cause chaos and have terrible consequences. By detecting a possible DDoS attack at an early stage, security measures that can reduce the impact of the attack can be taken immediately, and the likelihood of being a direct victim of the attack decreases. This study proposes a multi-stage learning model using a 1-dimensional convolutional neural network (1D-CNN) and decision tree-based classification to detect DDoS attacks in SDN-based SCADA systems effectively. A new dataset containing various attack scenarios on a specific experimental network topology was created to be used in the training and testing phases of this model. According to the experimental results of this study, the proposed model achieved a 97.8% accuracy rate in DDoS-attack detection. The proposed multi-stage learning model shows that high-performance results can be achieved in detecting DDoS attacks against SDN-based SCADA systems.

Use of terminal colostomy in a dog with rectal obstructive neoplasm

Colostomy is a surgical procedure in which the intestinal route is diverted to the abdomen through an intestinal stoma sutured to the skin. It is rarely reported in veterinary medicine due to postoperative complications such as suture dehiscence, infections, dermatitis, fecal incontinence, and mainly the tutor's difficulty in adapting to handling the bag. Surgical indication exists in cases of obstructive neoplasms in the colon and rectum, with the purpose of increasing the animal's quality of life by enabling the evasion of fecal content. The objective of this study is to report a surgical case of colostomy in a canine, Labrador, female and 13 years of age, as a possible procedure to treat signs of obstruction resulting from rectal neoplasm and to present the favorable and unfavorable factors of the procedure. The technique utilized was terminal colostomy with access to the abdominal cavity through the left flank. Despite tumor involvement, difficulty in management with the colostomy bag and the emergence of peristomal lesions, treatment resulted in increased patient survival and improvement of clinical signs of obstruction, and can thus be considered effective in cases of patients who need to divert the fecal route.

Management of Postmenopausal Osteoporosis by Moroccan General Practitioners: A Cross-Sectional Survey.

Despite the existence of effective treatments and prescribed therapeutic protocols, there is a lack of management of osteoporosis, resulting in increased secondary morbidity and mortality. The general practitioner (GP) is the first-line practitioner for the detection and management of osteoporosis. This study was conducted to explore the practices, knowledge, and difficulties in postmenopausal osteoporosis management reported by GPs. An anonymous questionnaire (19 questions) was created via Google Forms and distributed to 300 GPs via social networks (WhatsApp, Facebook, and Gmail). The survey results were automatically calculated on "Google Forms" and checked using SPSS.20 software. A total of 129 responses were received, representing a response rate of 43%. The majority of respondents were women (67.2%). The definition of osteoporosis was variable, with 51.6% defining it as a T-score of ≤-2.5 SD, 25.8% defining it as diffuse bone demineralization, and 12.1% defining it as a fracture after falling with low energy. Prolonged corticosteroid therapy was the most commonly indicated reason for measuring bone mineral density (BMD) (81.39%). The calcium phosphate balance was the most requested (90.1%). Vitamin D and calcium supplementation were reported by 74.41% and 54.26% of GPs, respectively. Fracture of the upper end of the femur was the main therapeutic indication (65.11%). Most GPs surveyed (73.3%) were unfamiliar with the fracture risk assessment tool (FRAX). Most of the GPs gave advice on fall prevention to their patients (83.72%), and 62.5% of GPs monitored their patients' height. Anti-osteoporosis treatment was maintained for 3 to 5 years by 44.96% of GPs. Our survey found that the practices and knowledge of GPs on osteoporosis vary widely and often deviate from the recommended standards. This highlights the need for more excellent education of GPs, due to their vital role in the management of osteoporosis.

Osteoarticular tuberculosis in infants: A diagnostic and management challenge

Objectives: Musculoskeletal manifestations of tuberculosis in infants are rare and different both in etiopathological mechanism and clinical presentation. Radiological diagnosis of osteoarticular tuberculosis (TB) in infants is tricky due to the various differentials of a cystic lesion. Literature also mention it only in isolated case reports. We carried out this study with an aim to collate and study patterns of osteoarticlular TB in the appendicular skeleton and to highlight the difficulties in diagnosis and management. Material and Methods: We retrospectively reviewed the data at our hospital over the past 8 years. Microbiologically confirmed osteoarticular tuberculosis affecting appendicular skeleton in children below 1 year of age were included in the study. Cases with spine involvement were excluded. The delay to diagnosis from the onset of symptoms, the initial diagnosis and treatment given were noted. The resolution of radiological presentation and occurrence of deformities at the final follow up (atleast 1 year) were noted. Results: During the study period, 8 infants were diagnosed to have osteoarticular tuberculosis with median age at presentation of 8.7 months (range 3 to 12 months). Average duration of follow up was 4 years (range 1 to 8 years). Cystic, Erosive, infiltrative, spina ventosa and mortar pestle were the radiological appearances found. Three of the 8 cases were referred as suspected malignancy. All but one case were vaccinated with BCG. Curettage and anti-tubercular therapy (ATT) were the treatment in all cases. Three cases with a delay in diagnosis of more than 2 months, developed complications: 1 had limb length discrepancy (LLD) due to physeal involvement, 1 developed angular deformity and 1 child had perthe’s disease as a sequelae. Conclusion: Osteoarticular tuberculosis is an increasing possibility, shockingly, even in infancy and should be a differential in an endemic country like India. A delay to diagnosis of even 2 months of this condition can lead to devastating complications. Being mindful of the diagnosis and early treatment gives rewarding results.