20-Gauge vs. 23-Gauge Vitrectomy, in Terms of Surgically Induced Astigmatism

OBJECTIVES To compare the post-operative (post-op) surgically induced mean astigmatism in patients undergoing 20-gauge- and 23-gauge vitrectomy. METHODOLOGY Sixty patients were enrolled. Relevant information was recorded in a Performa for each patient. Patients were randomly grouped into A (20-gauge) and B (23-gauge) groups. Astigmatism was recorded by a single technician using the same keratometer for all patients. A single surgeon operated on all patients. Post-operatively, all patients were re-examined after 1 week and 6 weeks, and their surgically induced astigmatism was recorded. RESULTSOf 60 patients, 58.6% were males, and 41.4% were females, with a mean age of 53.77 ± 9.63 years. The post-operative astigmatism difference between the two vitrectomy procedures was investigated. In the 20-gauge group, with 30 patients, the mean post-operative astigmatism difference was 2.21 D (±0.66 SD), with a standard error mean of 0.12. In the 23-gauge group, with 30 patients, the mean post-operative astigmatism difference was 0.74 D (±0.44 SD), with a standard error mean of 0.08. The degrees of freedom (df) were 58, and the standard error of the difference was 0.145. The t-value was calculated at 10.1504, and the p-value was found to be 0.001, indicating a significant difference. CONCLUSION The observation that the 20-gauge group displayed a notably higher mean difference in astigmatism than the 23-gauge group suggests a potential association between the choice of vitrectomy procedure and the extent of astigmatism alteration in post-operative outcomes

IMPACT OF CORONAVIRUS ON EDUCATION SYSTEM IN PAKISTAN: PROBLEMS AND SOLUTIONS

Background of the study: The sudden rise of COVID pandemic and its speedy spread around the globe affected almost all walks of life particularly the education system in Pakistan. The lockdown in the entire country and closure of all education institutes put a gape in teaching learning process. It made the teachers and students away from each other, thus physical interaction of students and teacher in classrooms became a dream for both the students as well for the teachers at secondary level. The parents of the students were very worried for the study loss of their children but they were helpless. Therefore, the purpose and focus of this research paper was on the evaluation of literature available internationally to see what the status of covid pandemic in the world is and what type of strategy they have adopted to cope with the problem. Method: The nature of this research is evaluative, as it has been mentioned in the above lines that focus was on the available literature, Online overview was also driven for data collection to evaluate it, analyze it and to see the result of the closure of educational institutes due to Covid pandemic and its impact on secondary education system of Pakistan. Results: Key results extracted from literature were: It affected all walks of life particularly the education system at large. It wasted the precious time of the students by halting physical interactive classrooms. ICT stepped in to replace physical classrooms with online classrooms but this new approach had many other problems like, lack of experience, many of the teaching staff as well as the students in ICT, availability of the electronic gadgets to all the teachers and students. Thus availability of the net facility to all the teachers and students in the country was also a problem. Conclusion: It was concluded that online classes were not as useful as physical interactive classes. It does not facilitate the entire stakeholder equally. Online classes have many flaws for instance, availability of the devices, experience of its usage, and net accessibility. In online class it is difficult for the teachers to have hold on the class like in physical classes

Performance Evaluation of Background Subtraction Techniques for Video Frames

The fundamental working of background subtraction is to identify the moving region by taking pixel-wise difference of the current frame from the previous one. The proposed study presents the comparison and implementation of different background subtraction techniques i.e., frame-difference method, mixture of Gaussian model 2 (MOG2) and k-nearest neighbor (KNN) for background subtraction. For all the three techniques, prior to segmentation, background modeling and then features extraction steps are performed. It is investigated that on the same dataset, frame-difference technique outperforms both MOG2 and KNN and achieve accuracy of 89.98%, recall of 94.43% precision 79.55% and F1-score of 81.42%

Deep learning applications in neuro-oncology

Deep learning (DL) is a relatively newer subdomain of machine learning (ML) with incredible potential for certain applications in the medical field. Given recent advances in its use in neuro-oncology, its role in diagnosing, prognosticating, and managing the care of cancer patients has been the subject of many research studies. The gamut of studies has shown that the landscape of algorithmic methods is constantly improving with each iteration from its inception. With the increase in the availability of high-quality data, more training sets will allow for higher fidelity models. However, logistical and ethical concerns over a prospective trial comparing prognostic abilities of DL and physicians severely limit the ability of this technology to be widely adopted. One of the medical tenets is judgment, a facet of medical decision making in DL that is often missing because of its inherent nature as a black box. A natural distrust for newer technology, combined with a lack of autonomy that is normally expected in our current medical practices, is just one of several important limitations in implementation. In our review, we will first define and outline the different types of artificial intelligence (AI) as well as the role of AI in the current advances of clinical medicine. We briefly highlight several of the salient studies using different methods of DL in the realm of neuroradiology and summarize the key findings and challenges faced when using this nascent technology, particularly ethical challenges that could be faced by users of DL

Op2Vec: An Opcode Embedding Technique and Dataset Design for End-to-End Detection of Android Malware

Android is one of the leading operating systems for smart phones in terms of market share and usage. Unfortunately, it is also an appealing target for attackers to compromise its security through malicious applications. To tackle this issue, domain experts and researchers are trying different techniques to stop such attacks. All the attempts of securing Android platform are somewhat successful. However, existing detection techniques have severe shortcomings, including the cumbersome process of feature engineering. Designing representative features require expert domain knowledge. There is a need for minimizing human experts' intervention by circumventing handcrafted feature engineering. Deep learning could be exploited by extracting deep features automatically. Previous work has shown that operational codes (opcodes) of executables provide key information to be used with deep learning models for detection process of malicious applications. The only challenge is to feed opcodes information to deep learning models. Existing techniques use one-hot encoding to tackle the challenge. However, the one-hot encoding scheme has severe limitations. In this paper, we introduce; (1) a novel technique for opcodes embedding, which we name Op2Vec, (2) based on the learned Op2Vec we have developed a dataset for end-to-end detection of android malware. Introducing the end-to-end Android malware detection technique avoids expert-intensive handcrafted features extraction, and ensures automation. Some of the recent deep learning-based techniques showed significantly improved results when tested with the proposed approach and achieved an average detection accuracy of 97.47%, precision of 0.976 and F1 score of 0.979

Measures to Mitigate Causative Factors of Budget Overrun in Malaysian Building Projects

Completion of a construction within planned budget is one of the main criterion of project success, however budget overrun has become a recurring phenomenon in construction industry. Budget overrun can cause multiple negative effects such as loos of economy, disputes among construction stakeholders, project abandonment, and drop in construction activities. This study aims to identify causes of budget overrun in Malaysian Building projects and then to establish mitigation measures for the identified main causes. Literature review, questionnaire survey and interviews were used in this study. Detailed literature review results in identification of 28 causes of budget overrun. The main causes of budget overrun in building projects in Malaysia were investigated through a questionnaire survey of 83 contractors, 57 clients, and 40 owners. The feedback of questionnaire survey was analyzed statistically. The significant causes of budget overrun were:  improper planning, variation in materials price, poor site management, lack of communication between parties, frequent design changes, incompetent contractors, mistakes during construction, shortage of site workers, delay in material procurement, and   low speed of decisions making.   After questionnaire survey, interviews with 16 construction exports were carried out in order to develop mitigation measures for the top ten significant causes. On the basis of interviews, a list of mitigation measures for each of the top ten significant causes were established. The findings of this study can be useful for construction practitioners in controlling budget overrun and to achieve project success

Effects of temperature and water purity on germination and yield of mungbean sprouts

Mungbean (Vigna radiata L. Wilczek) is a popular pulse crop, producing protein-rich food and nitrogen-rich residues. Mungbean sprouts were grown at different temperature levels of 10, 20 and 30°C in various water purities of 30 (distilled water), 100, 400, 700 and 1000 TDS (ppm). After keeping them in the germination chamber for 72 h, the percentage of germination, stem length and yield along with proximate composition were determined. The temperature was kept as main factor and water purity as the second. The experiment was replicated four times and the data obtained were analyzed using two factorial completely randomized design. The results showed that both the factors had significant (p<0.05) effect on the germination, stem length, yield as well as proximate composition. A temperature of 30°C and water with high purity of 30 TDS resulted in high emergence (69%), stem length (3.14 cm) and yield (70.1 g) as compared to the other treatments. Minimum germination (2.1%), stem length (0.11 cm) and yield (12.11 g) were recorded in samples kept at low temperature of 10°C and water purity with 1000 TDS. The mungbean seeds showed a very low plasticity to water purity, and that they were very susceptible to water impurities. It is concluded that, to prepare sprouts from mungbeans, it is necessary to germinate mungbean seeds them in water having high purity and temperature of 30oC for maximum germination, stem length and yield

Modelling, Simulation, and Control of a Flexible Space Launch Vehicle

Modern Space Launch Vehicles (SLVs), being slender in shape and due to the use of lightweight materials, are generally flexible in nature. This structural flexibility, when coupled with sensor and actuator dynamics, can adversely affect the control of SLV, which may lead to vehicle instability and, in the worst-case scenario, to structural failure. This work focuses on modelling and simulation of rigid and flexible dynamics of an SLV and its interactions with the control system. SpaceX's Falcon 9 has been selected for this study. The flexible modes are calculated using modal analysis in Ansys. High-fidelity nonlinear simulation is developed which incorporates the flexible modes and their interactions with rigid degrees of freedom. Moreover, linearized models are developed for flexible body dynamics, over the complete trajectory until the first stage's separation. Using classical control methods, attitude controllers, that keep the SLV on its desired trajectory, are developed, and multiple filters are designed to suppress the interactions of flexible dynamics. The designed controllers along with filters are implemented in the nonlinear simulation. Furthermore, to demonstrate the robustness of designed controllers, Monte-Carlo simulations are carried out and results are presented.Comment: Presented at 20th International Bhurban Conference on Applied Sciences and Technology (IBCAST), 202

Organotin(IV) esters of 4-maleimido-benzoic acid: synthesis, characterization and in vitro anti-leishmanial effects

Six new diorganotin(IV) esters with the general composition R2SnL2 (where R: Me(1), Et(2), Pr(3), Bu(4), Ph(5), Bz(6) and L(7): p-N-maleimido-benzoic acid) have been synthesized. Solid state FTIR and 119mSn Mössbauer spectra revealed bidentate behavior of L towards the diorganotin(IV) centre in the distorted octahedral products. ¹H, 13C and 119Sn NMR spectra in CDCl3 indicated hexacoordination in 1-4, penta-coordination of 5 in skew-trapezoidal geometry, and absence of hypercoordination in tetrahedral 6. Elemental analyses data have been found to corroborate the stoichiometry of the title organotin(IV) compounds. In vitro anti-leishmanial screenings have been conducted on five leishmanial strains of L. major, L. tropica, L. infantum, L. mex. mex. and L. donovani. Promising results have been observed and, on the basis of the data obtained during these assays, a structure-activity relationship has been suggested. The increasing size of the R groups in the {R2SnIV}2+ moieties increased the lipophilicity of organotin(IV) complexes, which thereby enhanced the anti-leishmanial activity